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School: University Of Michigan
Course: Dsp Design Lab
EECS452 Lab4 Pre-lab Mei Yang Q1. Answer: From the figure that has been generated, we can clearly see that the max gain is 60dB. Q2. Answer: From the matlab design, we can easily get that: a. 210 b. 35 Q3. Answer: For the passband, the difference is very
School: University Of Michigan
EECS 216 - Winter 2012 Pre Lab I Solutions (K. Winick, last revision Feb. 6, 2012) 1. (Problem 4.1) (a) ystep (t ) = (1 et /RC )u(t ) dystep (t ) dt RC 1 t /RC RC e = dystep (t ) dt 0 t >0 t <0 + ystep (t ) = 1 t >0 0 t <0 = u(t ) Also note that limt 0 y
School: University Of Michigan
Course: Digital Integrated Technology
H N % -L qj _\ Q q - - 4-ED c ) c) - L \ Hj c N ( s .& I o >< <.-.-. - . . , - I c It N l cA -1 i 1 Q c 0 aI <1 1- + 1 ; - r 0 a LA I a o. _ -p -t 1 k >( 0 )S + I N - P. ft I - r4\ (r\ p co> IoI. [ *7 ts 7oxc ) O/Q 4 / s+ SvI/yjf tJ5ij fi /),o6/e4- 2 1OS
School: University Of Michigan
Course: Digital Integrated Technology
) /-ik/f3 4- e Fa piu + e/A, sI p & II14 4/oi11 = I /-/Dq.2JAi 492q + i,t 1 A1 ,ww I (i&17q s)?Ivf I Q Z.4 ,c, C4c 3E) ,/ to -c )Y(.)L1)acO/ itl :d J(I UVfJ1141 1 . .4 I). ,OL4nDAC ,p,q do . 1 , af2L1P( [7 ,tQO U! :LA ft?1 c91 t) i 1 h e*Z 1 L, fa4L1qUI4
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 551/453 - HOMEWORK 1 Reading pertaining to the problem set: Chapter 1 of Laub Reading for next week: Chapter 2 Section 9.1 of Laub Problems marked with an asterisk (*) are for EECS 453 *Problem 1. Express the n m matrix A whose j th row equals j as a
School: University Of Michigan
Course: Math Meth Sig Proc
EECS551: HW2 SOLUTIONS Problem 1 T Let A = QQ be the eigendecomposition of A. Then we may write B = A 10I = QQT 10QQT (I = QQT since Q is orthogonal) = Q( 10I)QT (0.1) Notice that 10I is a diagonal matrix, and since Q is orthogonal, the right hand side of
School: University Of Michigan
EECS 280 Programming and Introductory Data Structures Midterm Exam Review Super-Fast-MultipleLectures-in-One 1 Exam Details Exam locations See the CTools announcement No notes no book no electronics only a writing tool 2 Exam Format Expected to be 5 Quest
School: University Of Michigan
Course: Machine Learn
OPTIMALITY CONDITIONS 1. Unconstrained Optimization 1.1. Existence. Consider the problem of minimizing the function f : Rn R where f is continuous on all of Rn : P min f (x). n xR As we have seen, there is no guarantee that f has a minimum value, or if it
School: University Of Michigan
#pragma once #include "thread.h" #include <ucontext.h> #include <memory> using namespace std; class thread:impl cfw_ public: impl() cfw_; ~impl() cfw_; unsigned threadID; ;
School: University Of Michigan
#include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include <ucontext.h> <vector> <iostream> <memory> <deque> <cassert> <utility> <exception> <unordered_map> "cpu_impl.h"
School: University Of Michigan
/* * thread.h - public interface to thread library * * This file should be included by the thread library and by application * programs that use the thread library. */ #ifndef _THREAD_H #define _THREAD_H static const unsigned int STACK_SIZE=262144; /
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; cv c; bool what = false; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; / what = true; / c.signal(); m.unlock(); void sayHow(void *a) cfw_ m.lock(); cout < "
School: University Of Michigan
Course: Math Meth Sig Proc
Cleves Corner Professor SVD By Cleve Moler Stanford computer science professor Gene Golub has done more than anyone to make the singular value decomposition one of the most powerful and widely used tools in modern matrix computation. from its SVD. Take 1
School: University Of Michigan
Course: Math Meth Sig Proc
The PageRank Citation Ranking: Bringing Order to the Web January 29, 1998 Abstract The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said o
School: University Of Michigan
Course: Math Meth Sig Proc
Chapter 7 Google PageRank The worlds largest matrix computation. (This chapter is out of date and needs a major overhaul.) One of the reasons why GoogleTM is such an eective search engine is the PageRankTM algorithm developed by Googles founders, Larry Pa
School: University Of Michigan
Course: Math Meth Sig Proc
(12) United States Patent Page US006285999B1 (10) Patent N0.: US 6,285,999 B1 (45) Date of Patent: Sep. 4, 2001 (54) METHOD FOR NODE RANKING IN A LINKED DATABASE (75) Inventor: Lawrence Page, Stanford, CA (US) (73) Assignee: The Board of Trustees of the
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
Foundations of processor design: finite state machines EECS 370 Introduction to Computer Organization Winter 2015 Robert Dick, Andrew Lukefahr, and Satish Narayanasamy EECS Department University of Michigan in Ann Arbor, USA Dick-Lukefahr-Narayanasamy, 2
School: University Of Michigan
Course: Power Electronics
E ECS 418: Power Electronics M id-term E xam O ctober 26, 2011 Name: _ _ _ Answer t he questions in the blue book provided. Be neat and concise in your answers. Circle your final answers. D on't forget to write your name in the blue-book. Q uestion 1 \ .)
School: University Of Michigan
Course: WEB DATA STRUCTURE
Web Essentials Lecture 1 Web Basics A brief history Transfer Content EECS 485 January 4, 2012 (some slides due to Dan Weld) Dewey Decimal system, library science 1960: Ted Nelson Xanadu Hypertext vision of WWW Focus on copyright, consistent (bidirectional
School: University Of Michigan
Course: WEB DATA STRUCTURE
Organization Lecture 15 Web Search Grab Bag! Today s class contains many search topics we have not yet explored 1 2 3 4 Crawler design Deduplication Inverted-index construction Distributed search architecture It s a bit of a grab-bag, but these are still-
School: University Of Michigan
RLC Circuits EECS 215: Intro. Second Order Circuits A second order circuit is characterized by a second order differential equation Resistors and two energy storage elements Determine voltage/current as a function of time Initial/final values of voltage/c
School: University Of Michigan
Course: Math Meth Sig Proc
K L- Pmke nka “QCW‘ \ Z ._ C\ v jvwl me21 <3“?- \ ' “p B Q Marks“ K 13 axoen S1 {ks {MM Um VIEWS) SVD \IEV—‘l lhvci‘cm‘n CHok CE C3: Do ( N6 Cs MT WnganW Chum; @ Gwen CCT 3 we (Lo-n m\‘t recover whim? cw * t cmg'ldgrcjikbh ")vbeAXB ‘ O.“ T C6: CQQC L_
School: University Of Michigan
Course: Math Meth Sig Proc
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School: University Of Michigan
University of Michigan WINTER 2011 EECS 401: Solution to Mid Term Examination I 1. TRUE. Consider the following argument: P (A B) C) = P (A C) (B C) (1) = P (A C) + P (B C) P (A C) (B C) (2) = P (A C) + P (B C) P (A B C), (3) where the rst equation follo
School: University Of Michigan
EECS 370 Midterm Exam 2 Fall 2012 Name: _ unique name: _ Sign the honor code: I have neither given nor received aid on this exam nor observed anyone else doing so. _ Scores: Problem # Part A Part B 1 2 3 4 5 Part C Total Points /30 /12 /12 /6 /10 /10 /20
School: University Of Michigan
Course: Circuits
Sample solutions EECS 314 Winter 2008 Final Exam Instructor: Alexander Ganago ganago@umich.edu Wednesday April 23, 2008, 10:30 AM 12:30 PM Exam rooms, according to the [first letter of] students' last names: A.K L.P R.Z 220 Chrysler Auditorium (our lectur
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
uniqname: _ EECS 280 Final Exam Fall 2012 This is a closed-book exam. There are 5 problems on 17 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that i
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS 280: Midterm Fall 2006 This is a closed-book exam; no notes are allowed. There are 5 problems on 17 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note al
School: University Of Michigan
EECS 216 EXAM #2 - Winter 2008 x(t) cos(3t)dt=: 1. Fourier series of x(t) is cos(t)+ 1 cos(2t)+ 1 cos(3t)+. . . Then 2 3 1 (a) 0 (b) 3 (c) (d) (e) 2 6 3 3 2 2. Impulse response of an LTI system with frequency response (j)2 +4(j)+4 is: (a) Nonc
School: University Of Michigan
Course: Digital Integrated Technology
H N % -L qj _\ Q q - - 4-ED c ) c) - L \ Hj c N ( s .& I o >< <.-.-. - . . , - I c It N l cA -1 i 1 Q c 0 aI <1 1- + 1 ; - r 0 a LA I a o. _ -p -t 1 k >( 0 )S + I N - P. ft I - r4\ (r\ p co> IoI. [ *7 ts 7oxc ) O/Q 4 / s+ SvI/yjf tJ5ij fi /),o6/e4- 2 1OS
School: University Of Michigan
Course: Digital Integrated Technology
) /-ik/f3 4- e Fa piu + e/A, sI p & II14 4/oi11 = I /-/Dq.2JAi 492q + i,t 1 A1 ,ww I (i&17q s)?Ivf I Q Z.4 ,c, C4c 3E) ,/ to -c )Y(.)L1)acO/ itl :d J(I UVfJ1141 1 . .4 I). ,OL4nDAC ,p,q do . 1 , af2L1P( [7 ,tQO U! :LA ft?1 c91 t) i 1 h e*Z 1 L, fa4L1qUI4
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 551/453 - HOMEWORK 1 Reading pertaining to the problem set: Chapter 1 of Laub Reading for next week: Chapter 2 Section 9.1 of Laub Problems marked with an asterisk (*) are for EECS 453 *Problem 1. Express the n m matrix A whose j th row equals j as a
School: University Of Michigan
Course: Math Meth Sig Proc
EECS551: HW2 SOLUTIONS Problem 1 T Let A = QQ be the eigendecomposition of A. Then we may write B = A 10I = QQT 10QQT (I = QQT since Q is orthogonal) = Q( 10I)QT (0.1) Notice that 10I is a diagonal matrix, and since Q is orthogonal, the right hand side of
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW 3 Reading for next week: Chapter 2 and Chapter 3 of Laub EECS 551 students solve all problems. EECS 453 students only solve problems with a *. *Problem 1. This what is known about the dietary habits of the mythical Michigan Wolverine who
School: University Of Michigan
Course: DISCRETE MATHEMATICS
EECS 203: DISCRETE MATHEMATICS Homework 9 Solutions 1. (9 points) If R V V is a binary relation over V then R1 (the inverse) is dened as: (x, y ) R if and only if (y, x) R1 . Prove or disprove the following: (a) If R is transitive & reexive then R R1 is a
School: University Of Michigan
Course: Dsp Design Lab
EECS452 Lab4 Pre-lab Mei Yang Q1. Answer: From the figure that has been generated, we can clearly see that the max gain is 60dB. Q2. Answer: From the matlab design, we can easily get that: a. 210 b. 35 Q3. Answer: For the passband, the difference is very
School: University Of Michigan
Course: Embedded Control Systems
EECS 461 Spring 2014 Lab 1: Familiarization and Digital I/O 1 Overview The purpose of this lab is to familiarize you with the hardware and software used in EECS 461. For this class we will be using a 32-bit oating-point Freescale MPC5553 microcontroller r
School: University Of Michigan
Course: Dsp Design Lab
Pre-lab questions: Q1. Consider the logic statement (A*B)+(C*A) a. Write the truth table for that logic statement b. Draw the gates that implement that logic statement (without simplification). A, B 00 01 10 11 C=0 0 0 0 1 C=1 1 1 0 1 Q2. Consider a 2-to-
School: University Of Michigan
EECS 215 Lab Supplementary Materials / Op Amp Lab Cover page Op Amp Lab Report Students Name _ Date of Lab Work _ I have neither given nor received aid on this report, nor have I concealed any violations of the Honor Code. _ (students signature) Lab Secti
School: University Of Michigan
Course: Parallel Computing
Serial Quicksort Quicksort is an important sorting algorithm. Given an array A(1:n) of items to be sorted, Quicksort(i,j,A) sorts the items in positions i . . . j. To sort the entire array, the main program calls Quicksort(1,n,A). Quicksort(i,j,A): If j
School: University Of Michigan
EECS 551/EECS 453 EIG/SVD & what you can do with it 1. Sensor localization Multidimensional scaling http:/www.mathworks.com/products/statistics/demos.html?file=/products/demos/shipping/stats/cmdscaledemo.html MATLABs cmdscale.m Cmdscale.m 2. Image Compre
School: University Of Michigan
Course: PROBABILITY
Chapter 1 Sigma-Algebras 1.1 Denition Consider a set X . A algebra F of subsets of X is a collection F of subsets of X satisfying the following conditions: (a) F (b) if B F then its complement B c is also in F (c) if B1 , B2 , . is a countable collection
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: Googles Page-Rank algorithm In MATLAB, load the eecs.umich.edu adjacency matrix you produced by running surfer.m. Please download the pagerank_demo.zip file from Canvas under files\demos\pagerank section and unzip it into a working folder. I
School: University Of Michigan
Course: Math Meth Sig Proc
Thursday, September 18, 2014 1:27 PM Discussion Week 3 Page 1 Thursday, September 18, 2014 1:40 PM Discussion Week 3 Page 2 Thursday, September 18, 2014 1:45 PM Discussion Week 3 Page 3 Thursday, September 18, 2014 1:55 PM Discussion Week 3 Page 4 Thursda
School: University Of Michigan
Course: Math Meth Sig Proc
Discussion 2 Follow Up David Hiskens September 21, 2015 Eigendecomposition of Non-Diagonal Matrix There was a request for an example of an eigendecomposition in which the eigenvectors were not trivially the columns of the identity matrix. Consider the fol
School: University Of Michigan
Course: Comp. Vision
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. PAMI-8, NO. 6, NOVEMBER 1986 679 A Computational Approach to Edge Detection JOHN CANNY, MEMBER, IEEE Abstract-This paper describes a computational approach to edge detection. The success
School: University Of Michigan
Course: Comp. Vision
An Introduction to Projective Geometry for computer vision Stan Birch eld 1 Introduction We are all familiar with Euclidean geometry and with the fact that it describes our threedimensional world so well. In Euclidean geometry, the sides of objects have l
School: University Of Michigan
Course: Intr Art Intell
syllabus-F15.xlsx 9/4/15 EECS 492: Artificial Intelligence topic read before class 9/8 9/10 What is AI? Agents and environments chapter 1 (29p) chapter 2 (22p) 9/15 9/17 State spaces and search Beyond classical search chapter 3 (45p) chapter 4 (34p) 9/22
School: University Of Michigan
Course: Intr Art Intell
EECS 492: Introduction to Artificial Intelligence Fundamental concepts of AI, organized around the task of building computational agents. Core topics include search, logic, representation and reasoning, automated planning, representation and decision maki
School: University Of Michigan
Course: Comp. Vision
EECS 598-01 Special Topic Foundations of Computer Vision Fall 2015 MW 12:00-1:30PM in 1005 DOW Course Overview: Computer Vision seeks to extract useful information from images, video and other visual content. This course will introduce the breadth of mode
School: University Of Michigan
Course: Comp. Vision
EECS 598-01 Foundations of Computer Vision Electrical Engineering and Computer Science University of Michigan Syllabus for Fall 2015 Last updated: 8 September 2015 Instructor: Jason Corso (jjcorso) Course Webpage: http:/web.eecs.umich.edu/jjcorso/t/598F15
School: University Of Michigan
Course: Comp. Vision
Week Monday Wednesday 9/7 No Class: Before Term 1: Introduction 9/14 2: Images as Functions 3: Image Operations 9/21 4: Geometric Invariance 5: Case Study on Geometric Invariance by Local Features: Rotation Invariance 9/28 6: Case Study on Geometric Invar
School: University Of Michigan
Course: Parallel Computing
Parallel Computing: EECS 587 Quentin F. Stout 3605 CSE 763-1518 qstout@umich.edu www.eecs.umich.edu/~qstout Texts: None, but some computer manuals will be used, and there will be various papers, book excerpts, and web resources. Course Overview: The cours
School: University Of Michigan
Course: Dsp Design Lab
EECS452 Lab4 Pre-lab Mei Yang Q1. Answer: From the figure that has been generated, we can clearly see that the max gain is 60dB. Q2. Answer: From the matlab design, we can easily get that: a. 210 b. 35 Q3. Answer: For the passband, the difference is very
School: University Of Michigan
EECS 216 - Winter 2012 Pre Lab I Solutions (K. Winick, last revision Feb. 6, 2012) 1. (Problem 4.1) (a) ystep (t ) = (1 et /RC )u(t ) dystep (t ) dt RC 1 t /RC RC e = dystep (t ) dt 0 t >0 t <0 + ystep (t ) = 1 t >0 0 t <0 = u(t ) Also note that limt 0 y
School: University Of Michigan
Course: Digital Integrated Technology
H N % -L qj _\ Q q - - 4-ED c ) c) - L \ Hj c N ( s .& I o >< <.-.-. - . . , - I c It N l cA -1 i 1 Q c 0 aI <1 1- + 1 ; - r 0 a LA I a o. _ -p -t 1 k >( 0 )S + I N - P. ft I - r4\ (r\ p co> IoI. [ *7 ts 7oxc ) O/Q 4 / s+ SvI/yjf tJ5ij fi /),o6/e4- 2 1OS
School: University Of Michigan
Course: Digital Integrated Technology
) /-ik/f3 4- e Fa piu + e/A, sI p & II14 4/oi11 = I /-/Dq.2JAi 492q + i,t 1 A1 ,ww I (i&17q s)?Ivf I Q Z.4 ,c, C4c 3E) ,/ to -c )Y(.)L1)acO/ itl :d J(I UVfJ1141 1 . .4 I). ,OL4nDAC ,p,q do . 1 , af2L1P( [7 ,tQO U! :LA ft?1 c91 t) i 1 h e*Z 1 L, fa4L1qUI4
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 551/453 - HOMEWORK 1 Reading pertaining to the problem set: Chapter 1 of Laub Reading for next week: Chapter 2 Section 9.1 of Laub Problems marked with an asterisk (*) are for EECS 453 *Problem 1. Express the n m matrix A whose j th row equals j as a
School: University Of Michigan
Course: Math Meth Sig Proc
EECS551: HW2 SOLUTIONS Problem 1 T Let A = QQ be the eigendecomposition of A. Then we may write B = A 10I = QQT 10QQT (I = QQT since Q is orthogonal) = Q( 10I)QT (0.1) Notice that 10I is a diagonal matrix, and since Q is orthogonal, the right hand side of
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW 3 Reading for next week: Chapter 2 and Chapter 3 of Laub EECS 551 students solve all problems. EECS 453 students only solve problems with a *. *Problem 1. This what is known about the dietary habits of the mythical Michigan Wolverine who
School: University Of Michigan
Course: DISCRETE MATHEMATICS
EECS 203: DISCRETE MATHEMATICS Homework 9 Solutions 1. (9 points) If R V V is a binary relation over V then R1 (the inverse) is dened as: (x, y ) R if and only if (y, x) R1 . Prove or disprove the following: (a) If R is transitive & reexive then R R1 is a
School: University Of Michigan
Course: Database Mgt Syst
EECS 484 Homework #5 Question 1 Consider the following relational schema and SQL query: Students(sid, sname, gpa) Takes(sid, cid) Class(cid, cname, ctype) SELECT S.sname, C.cname FROM Students S, Takes T, Class C WHERE S.sid = T.sid AND T.cid = C.cid AND
School: University Of Michigan
Course: WEB DATA STRUCTURE
Web Essentials Lecture 1 Web Basics A brief history Transfer Content EECS 485 January 4, 2012 (some slides due to Dan Weld) Dewey Decimal system, library science 1960: Ted Nelson Xanadu Hypertext vision of WWW Focus on copyright, consistent (bidirectional
School: University Of Michigan
Course: ML
EECS445: Introduction to Machine Learning, Fall 2014 Homework #1 Due date: 5pm on 9/23 (Tuesday) Reminder: While you are encouraged to think about problems in small groups, all written solutions must be independently generated. Please type or hand-write s
School: University Of Michigan
Course: WEB DATA STRUCTURE
Organization Lecture 15 Web Search Grab Bag! Today s class contains many search topics we have not yet explored 1 2 3 4 Crawler design Deduplication Inverted-index construction Distributed search architecture It s a bit of a grab-bag, but these are still-
School: University Of Michigan
EECS 203, Discrete Mathematics Your last name (print): Winter 2010, University of Michigan, Ann Arbor Your rst name (print): Circle your lecture section: 1 (TTH9) 2 (TTH12) Circle your discussion section: 011 (Mandava M1:30) 012 (Wu F3:30) 013 (Wu W10:30)
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW1 SOLUTIONS Problem 1 (*) m Let e R be a vector with ei = 1 for i = 1, . . . , m. Let x Rn be a vector with xj = j for j = 1, . . . , n. Then the desired n m matrix whose j-th row equals j is given by the outer-product xeT . In MATLAB we w
School: University Of Michigan
University of Michigan WINTER 2011 EECS 401: Solution to Mid Term Examination I 1. TRUE. Consider the following argument: P (A B) C) = P (A C) (B C) (1) = P (A C) + P (B C) P (A C) (B C) (2) = P (A C) + P (B C) P (A B C), (3) where the rst equation follo
School: University Of Michigan
Course: Computer Vision
EECS 442 Computer Vision, Homework 2 Due on , Please submit your assignment on ctools 1 [30 points] Fundamental Matrix In this question, you will explore some properties of fundamental matrix and derive a minimal parameterization for it. (a) [10 points] S
School: University Of Michigan
Course: Embedded Control Systems
EECS 461 Spring 2014 Lab 1: Familiarization and Digital I/O 1 Overview The purpose of this lab is to familiarize you with the hardware and software used in EECS 461. For this class we will be using a 32-bit oating-point Freescale MPC5553 microcontroller r
School: University Of Michigan
Course: Database Mgt Syst
EECS 484 Homework #5 Question 1 Consider the following relational schema and SQL query: Students(sid, sname, gpa) Takes(sid, cid) Class(cid, cname, ctype) SELECT S.sname, C.cname FROM Students S, Takes T, Class C WHERE S.sid = T.sid AND T.cid = C.cid AND
School: University Of Michigan
Course: Digital Integrated Technology
University of Michigan Department of Electrical Engineering and Computer Science EECS 523 HW#4 Fall 2012 Due (at the beginning of the class): October 30 1- A 0.5m thin poly has been implanted with both phosphorus and boron impurities with a dose of 6 x 10
School: University Of Michigan
Course: Data Structures And Algorithms
UniversityofMichigan EECS281:DataStructuresandAlgorithms Homework1 Fall2015 Assigned : TuesdaySep15,2015,11:59PM Due : ThursdaySep24,201511:59PM Instructions : Homework1isworth25totalpoints.EnteryourresponsestoProblems 14ontheCToolsTestCenter.Problem5must
School: University Of Michigan
EECS 280 Programming and Introductory Data Structures Midterm Exam Review Super-Fast-MultipleLectures-in-One 1 Exam Details Exam locations See the CTools announcement No notes no book no electronics only a writing tool 2 Exam Format Expected to be 5 Quest
School: University Of Michigan
EECS 216 Winter 2012 Lab 1: LTI Systems Part II: In-lab & Post-lab Assignment Department of Electrical Engineering & Computer Science University of Michigan c Kim Winick 2008 1 Laboratory Task Description Unless otherwise specied, it will be assumed that
School: University Of Michigan
Course: Introduction To MEMS
EECS 414 Introduction to MEMS Homework #3 Total: 180 Points Fall 2007 Handed Out: Due: Friday Sept. 21, 2007 Friday Sept. 28, 2007 1. This problem deals with etching of the silicon device shown below. The figure shows the cross section and the t
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW3 SOLUTIONS Problem 1 (*) The transition probability matrix is Cheese 0 1/2 1/2 Cheese P = Grapes Lettuce Grapes 4/10 1/10 5/10 Lettuce 6/10 4/10 0 T Let = 1 2 3 be the equilibrium distribution of the states (Cheese, Grapes, Lettuce),
School: University Of Michigan
RLC Circuits EECS 215: Intro. Second Order Circuits A second order circuit is characterized by a second order differential equation Resistors and two energy storage elements Determine voltage/current as a function of time Initial/final values of voltage/c
School: University Of Michigan
EECS 370 Midterm Exam 2 Fall 2012 Name: _ unique name: _ Sign the honor code: I have neither given nor received aid on this exam nor observed anyone else doing so. _ Scores: Problem # Part A Part B 1 2 3 4 5 Part C Total Points /30 /12 /12 /6 /10 /10 /20
School: University Of Michigan
EECS 314 Winter 2008 Homework set 8 Student's name _ Discussion section # _ (Last, First, write legibly, use ink) (use ink) Instructor is not responsible for grading and entering scores for HW papers lacking clear information in the required field
School: University Of Michigan
EECS 203, Discrete Mathematics Winter 2007, University of Michigan, Ann Arbor Problem Set 5 Problems from the Textbook 9.1: 24[E] 9.2: 58[M] 9.3: 32[M], 68[M] 9.4: 16[E] 2.4: 26[C], 38[E] * Additional Problems Required for All Students Problem A5.
School: University Of Michigan
EECS 203: Homework 1 Solutions Section 1.1 1. (E) 8bef b) You do not miss the final exam if and only if you pass the course. e) If you have the flu then you do not pass the course, or if you miss the final examination then you do not pass the course. f) Y
School: University Of Michigan
Course: Circuits
Sample solutions EECS 314 Winter 2008 Final Exam Instructor: Alexander Ganago ganago@umich.edu Wednesday April 23, 2008, 10:30 AM 12:30 PM Exam rooms, according to the [first letter of] students' last names: A.K L.P R.Z 220 Chrysler Auditorium (our lectur
School: University Of Michigan
EECS 280 Programming and Introductory Data Structures Midterm Exam Review Super-Fast-MultipleLectures-in-One 1 Exam Details Exam locations See the CTools announcement No notes no book no electronics only a writing tool 2 Exam Format Expected to be 5 Quest
School: University Of Michigan
Course: Machine Learn
OPTIMALITY CONDITIONS 1. Unconstrained Optimization 1.1. Existence. Consider the problem of minimizing the function f : Rn R where f is continuous on all of Rn : P min f (x). n xR As we have seen, there is no guarantee that f has a minimum value, or if it
School: University Of Michigan
#pragma once #include "thread.h" #include <ucontext.h> #include <memory> using namespace std; class thread:impl cfw_ public: impl() cfw_; ~impl() cfw_; unsigned threadID; ;
School: University Of Michigan
#include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include <ucontext.h> <vector> <iostream> <memory> <deque> <cassert> <utility> <exception> <unordered_map> "cpu_impl.h"
School: University Of Michigan
/* * thread.h - public interface to thread library * * This file should be included by the thread library and by application * programs that use the thread library. */ #ifndef _THREAD_H #define _THREAD_H static const unsigned int STACK_SIZE=262144; /
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; cv c; bool what = false; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; / what = true; / c.signal(); m.unlock(); void sayHow(void *a) cfw_ m.lock(); cout < "
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m1; void child(void *b) cfw_ m1.unlock(); cout < "child start" < endl; cout < "child end" < endl; void parent(void *a) cfw_ cout < "parent start" < endl; thread t1(chil
School: University Of Michigan
#include #include #include #include <iostream> <cstdlib> "thread.h" <stdexcept> using namespace std; mutex m; cv c; void brother()cfw_ cout < "brother start\n"; try cfw_ m.unlock(); cout < "Failed to catch error: unlocking while parent hold the lock\n";
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; void sayWhat(void *a) cfw_ m.lock(); cout < "What start?\n"; m.unlock(); thread:yield(); m.lock(); cout < "What end?\n"; m.unlock(); void sayHow(void *a) cfw_ m.lock
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; m.unlock(); void sayHow(void *a) cfw_ m.lock(); cout < "How?\n"; m.unlock(); void parent(void *a) cfw_ m.lock
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; cv c; bool what = false; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; what = true; c.signal(); m.unlock(); void sayHow(void *a) cfw_ m.lock(); while ( !wha
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; void sayWhat(void *a) cfw_ cout < "What?\n"; void sayHow(void *a) cfw_ cout < "How?\n"; void parent(void *a) cfw_ cout < "nope" < endl; thread t1 ( (thread_startfunc_t) sayW
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; cv c; bool what = false; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; what = true; c.signal(); m.unlock(); void sayHow(void *a) cfw_ m.lock(); while ( !wha
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; int i = 0; void sayHow(void *a) cfw_ while (i=0) cfw_ i = 1; thread:yield(); cout < "How?\n"; cout < "How?\n"; void parent(void *a) cfw_ cout < "nope" < endl; thread t1( (th
School: University Of Michigan
#include #include #include #include <iostream> <cstdlib> <memory> "thread.h" #define THREADNUM 100 using namespace std; int what = 0; mutex m; cv oneCv; void sayWhat(void *a) cfw_ m.lock(); cout < "waiting.\n"; what+; oneCv.signal(); m.unlock(); (thread *
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" #define THREADNUM 5 using namespace std; mutex m; cv c; int howStart = 0; bool what = false; void sayWhat(void *a) cfw_ while ( howStart != THREADNUM ); m.lock(); cout < "What\n"; what = true; c.s
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; void parent(void *a) cfw_ m.lock(); cout < "nope" < endl; m.unlock(); int main() cfw_ cpu:boot(1, (thread_startfunc_t) parent, NULL, false, false, 0);
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; void parent(void *a) cfw_ cout < "nope" < endl; int main() cfw_ cpu:boot(1, (thread_startfunc_t) parent, NULL, true, true, 0);
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; void sayWhat(void *a) cfw_ cout < "What?\n"; void parent(void *a) cfw_ cout < "nope" < endl; thread t1 ( (thread_startfunc_t) sayWhat, NULL); cout < "nope done!\n"; int main
School: University Of Michigan
#include #include #include #include #include <iostream> <cstdlib> "thread.h" <exception> <stdexcept> #define THREADNUM 5 using namespace std; mutex m; void child(void *b) cfw_ try cfw_ m.unlock(); catch ( const runtime_error ) cfw_ cout < "catched!" < en
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; void sayWhat(void *a) cfw_ m.lock(); cout < "What?\n"; thread:yield(); cout < "What?\n"; m.unlock(); void sayHow(void *a) cfw_ m.lock(); cout < "How?\n"; thread:yiel
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; #define THREADNUM 10 mutex m; void parent(void *a) cfw_ cout < "nope" < endl; for ( int i = 0; i < THREADNUM; i + ) cfw_ m.lock(); m.unlock(); cout < "nope done!\n"; int mai
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; void parent(void *a) cfw_ cout < "I wanna lock forever!" < endl; m.lock(); m.lock(); m.lock(); cout < "nope" < endl; int main() cfw_ cpu:boot(1, (thread_startfunc_t)
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" #define THREADNUM 5 using namespace std; mutex m; cv c; int howStart = 0; bool what = false; void sayWhat(void *a) cfw_ while ( howStart != THREADNUM ); m.lock(); cout < "What\n"; what = true; c.b
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" #define THREADNUM 5 using namespace std; mutex m; cv c; int howStart = 0; bool what = false; void sayWhat(void *a) cfw_ c.signal(); c.broadcast(); while ( howStart != THREADNUM ); m.lock(); cout <
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; int i = 0; void sayWhat(void *a) cfw_ cout < "What?\n"; (thread *) a)->join(); cout < "What?\n"; void sayHow(void *a) cfw_ while (i=0) cfw_ i = 1; thread:yield(); cout < "Ho
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; cv c; void loop(void* a)cfw_ intptr_t arg = (intptr_t) a; cout < "loop start, thread " < arg < " yield" < endl; thread:yield(); m.lock(); c.wait(m); cout < "thread "
School: University Of Michigan
#include <iostream> #include <cstdlib> #include "thread.h" using namespace std; mutex m; bool firstDone = false; void first(void *a) cfw_ cout < "thread first waiting for lock!\n"; m.lock(); cout < "thread first get locked then unlocked!\n"; m.unlock();
School: University Of Michigan
#include #include #include #include <stdexcept> <iostream> <cstdlib> "thread.h" #define WOMEN 0 #define MEN 1 using namespace std; bool start = false; mutex bathroom_lock; cv waitStart; cv men, women; int active_men = 0; int active_women = 0; int waiting_
School: University Of Michigan
#include #include #include #include #include #include #include #include <iostream> <fstream> "thread.h" "cpu.h" <vector> <string> <climits> <cmath> #define MAXCOKE 20 using namespace std; mutex m; cv waitConsumers; cv waitProducers; int numCokes = 0; int
School: University Of Michigan
Course: Math Meth Sig Proc
Cleves Corner Professor SVD By Cleve Moler Stanford computer science professor Gene Golub has done more than anyone to make the singular value decomposition one of the most powerful and widely used tools in modern matrix computation. from its SVD. Take 1
School: University Of Michigan
Course: Math Meth Sig Proc
The PageRank Citation Ranking: Bringing Order to the Web January 29, 1998 Abstract The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said o
School: University Of Michigan
Course: Math Meth Sig Proc
Chapter 7 Google PageRank The worlds largest matrix computation. (This chapter is out of date and needs a major overhaul.) One of the reasons why GoogleTM is such an eective search engine is the PageRankTM algorithm developed by Googles founders, Larry Pa
School: University Of Michigan
Course: Math Meth Sig Proc
(12) United States Patent Page US006285999B1 (10) Patent N0.: US 6,285,999 B1 (45) Date of Patent: Sep. 4, 2001 (54) METHOD FOR NODE RANKING IN A LINKED DATABASE (75) Inventor: Lawrence Page, Stanford, CA (US) (73) Assignee: The Board of Trustees of the
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
Foundations of processor design: finite state machines EECS 370 Introduction to Computer Organization Winter 2015 Robert Dick, Andrew Lukefahr, and Satish Narayanasamy EECS Department University of Michigan in Ann Arbor, USA Dick-Lukefahr-Narayanasamy, 2
School: University Of Michigan
Course: Power Electronics
E ECS 418: Power Electronics M id-term E xam O ctober 26, 2011 Name: _ _ _ Answer t he questions in the blue book provided. Be neat and concise in your answers. Circle your final answers. D on't forget to write your name in the blue-book. Q uestion 1 \ .)
School: University Of Michigan
IV. ESTIMATOR Objective: ML estimator Where P is positive since the elements of P (compartmental parameters, concentrations, myocardial thicknesses, and endocardial radii) are physically positive, and with assumption of Poisson measurement noise where k i
School: University Of Michigan
IEEE TRANSACTIONS ON MEDICAL IMAGING, V OL 13. NO. 2 , JUNE 1994 217 Model-Based Estimation for Dynamic Cardiac Studies Using ECT Ping-Chun Chiao, W . L eslie Rogers, Neal H. Clinthorne, Jeffrey A. Fessler, and Alfred 0. Hero Abstract-In this paper, we de
School: University Of Michigan
Course: WEB DATA STRUCTURE
Web Essentials Lecture 1 Web Basics A brief history Transfer Content EECS 485 January 4, 2012 (some slides due to Dan Weld) Dewey Decimal system, library science 1960: Ted Nelson Xanadu Hypertext vision of WWW Focus on copyright, consistent (bidirectional
School: University Of Michigan
Course: WEB DATA STRUCTURE
Organization Lecture 15 Web Search Grab Bag! Today s class contains many search topics we have not yet explored 1 2 3 4 Crawler design Deduplication Inverted-index construction Distributed search architecture It s a bit of a grab-bag, but these are still-
School: University Of Michigan
RLC Circuits EECS 215: Intro. Second Order Circuits A second order circuit is characterized by a second order differential equation Resistors and two energy storage elements Determine voltage/current as a function of time Initial/final values of voltage/c
School: University Of Michigan
Course: Math Meth Sig Proc
K L- Pmke nka “QCW‘ \ Z ._ C\ v jvwl me21 <3“?- \ ' “p B Q Marks“ K 13 axoen S1 {ks {MM Um VIEWS) SVD \IEV—‘l lhvci‘cm‘n CHok CE C3: Do ( N6 Cs MT WnganW Chum; @ Gwen CCT 3 we (Lo-n m\‘t recover whim? cw * t cmg'ldgrcjikbh ")vbeAXB ‘ O.“ T C6: CQQC L_
School: University Of Michigan
Course: Math Meth Sig Proc
Produced with a Trial Version of PDF Annotator - www.PDFAnnotator.com
School: University Of Michigan
Course: Machine Learn
Unconstrained Optimization Tuesday, September 8, 2015 8:39 PM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7 Lecture Notes Page 8 Lecture Notes Page 9
School: University Of Michigan
Course: Machine Learn
Thursday, September 10, 2015 11:59 AM Lecture Notes Page 1 Lecture Notes Page 2 3 2 1 0 -1 -2 -3 -3 Lecture Notes Page 3 -2 -1 0 1 2 3 4 5 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7
School: University Of Michigan
Course: Machine Learn
SML Tuesday, September 8, 2015 11:20 AM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7 Lecture Notes Page 8
School: University Of Michigan
Course: Comp. Vision
Foundations of Computer Vision Introduction EECS 598-01 Fall 2015! ! http:/web.eecs.umich.edu/~jjcorso/t/598F15! https:/umich.instructure.com/courses/9801! ! Instructor: Jason Corso! jjcorso@eecs.umich.edu! Materials on these slides have come from many so
School: University Of Michigan
Course: Comp. Vision
Scale Invariance and Automatic Scale Selection EECS59801Fall2015 FoundationsofComputerVision Instructor:JasonCorso(jjcorso) web.eecs.umich.edu/~jjcorso/t/598F15 Readings:SZ4.2,4.3;FP5 Date:9/28/14 Materialsontheseslideshavecomefrommanysourcesinadditiontom
School: University Of Michigan
Course: Comp. Vision
Case Study for Geometric Invariance Corner Features EECS 598-01 Fall 2015! Foundations of Computer Vision! ! Instructor: Jason Corso (jjcorso)! web.eecs.umich.edu/~jjcorso/t/598F15! Readings: SZ 4.2, 4.3 (FP 5)! Date: 9/21-23/15! ! Materials on these slid
School: University Of Michigan
Course: Comp. Vision
J. J. Corso, University of Michigan 2 Images as Functions Operations on Images With our functional interpretation of images, we can bring to bear the full-range of mathematical aspects of functions both in terms of practice and theory. For example, we can
School: University Of Michigan
Course: Comp. Vision
Images as Functions EECS 598-001 Foundations of Computer Vision Fall 2015 Jason Corso University of Michigan September 14, 2015 Images are the primary data source that we focus on in this course. However, we do not restrict ourselves to images of the natu
School: University Of Michigan
Course: Comp. Vision
Domain Operations EECS 598-01 Fall 2015! Foundations of Computer Vision! ! http:/web.eecs.umich.edu/~jjcorso/t/598F15! ! Instructor: Jason Corso! jjcorso@eecs.umich.edu! Materials on these slides have come from many sources in addition to myself; I am inn
School: University Of Michigan
Course: Machine Learn
Linear Regression Friday, September 12, 2014 1:56 PM Lecture Notes Page 1 2.5 2 1.5 1 0.5 Lecture Notes Page 2 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Lecture Notes Page 3 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7
School: University Of Michigan
Course: Machine Learn
Bayes Classifiers Thursday, September 10, 2015 11:59 AM Lecture Notes Page 1 Lecture Notes Page 2 3 2 1 0 -1 -2 -3 -3 Lecture Notes Page 3 -2 -1 0 1 2 3 4 5 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7
School: University Of Michigan
Course: Machine Learn
Separating Hyperplanes Thursday, September 11, 2014 12:07 PM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7 Lecture Notes Page 8 Lecture Notes Page 9 Lectu
School: University Of Michigan
Course: Machine Learn
Logistic Regression Thursday, September 4, 2014 6:55 PM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4 Lecture Notes Page 5 Lecture Notes Page 6 Lecture Notes Page 7 Lecture Notes Page 8
School: University Of Michigan
Course: Machine Learn
LDA Thursday, September 4, 2014 4:28 PM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4
School: University Of Michigan
Course: Machine Learn
6.867 Section 3: Classication Contents 1 Intro 2 2 Representation 2 3 Probabilistic models 3.1 Estimating Pr(X, Y) . . . . . . . . . . . . . . . . . . 3.1.1 Linear discriminant analysis . . . . . . . . 3.1.2 Factoring the class conditional probability 3.1
School: University Of Michigan
Course: Machine Learn
Nave Bayes Tuesday, September 2, 2014 4:38 PM Lecture Notes Page 1 Lecture Notes Page 2 Lecture Notes Page 3 Lecture Notes Page 4
School: University Of Michigan
Course: Machine Learn
EECS 545 Fall 2014 Tuesday, September 2, 2014 4:14 PM 02_unconstrained Page 1 02_unconstrained Page 2 02_unconstrained Page 3 02_unconstrained Page 4 02_unconstrained Page 5 02_unconstrained Page 6 02_unconstrained Page 7 02_unconstrained Page 8 02_uncons
School: University Of Michigan
Course: Data Structures And Algorithms
EECS 281: Data Structures and Algorithms Bitcoin algorithms Bitcoin technologies Use technology: cryptographic hash functions digital signatures distributed peer to peer network To build a digital cash system that is: anonymous decentralized reliabl
School: University Of Michigan
Course: Data Structures And Algorithms
Minimal Spanning Tree Strikes Back Implementing Prims algorithm Comparing Prims to Kruskals Union-Find The Minimal Spanning Tree Problem Given: edge-weighted undirected graph G = (V,E) Find: subgraph T=(V,E), EE such that All vertices are pair-wise conne
School: University Of Michigan
Course: Data Structures And Algorithms
EECS 281: Data Structures and Algorithms Cryptography Background Digital Cryptography Many useful applications: Private communication Proof of identity Fraud prevention Digitally signed documents Digital cash Data All data consists of strings of bit
School: University Of Michigan
University of Michigan WINTER 2011 EECS 401: Solution to Mid Term Examination I 1. TRUE. Consider the following argument: P (A B) C) = P (A C) (B C) (1) = P (A C) + P (B C) P (A C) (B C) (2) = P (A C) + P (B C) P (A B C), (3) where the rst equation follo
School: University Of Michigan
EECS 370 Midterm Exam 2 Fall 2012 Name: _ unique name: _ Sign the honor code: I have neither given nor received aid on this exam nor observed anyone else doing so. _ Scores: Problem # Part A Part B 1 2 3 4 5 Part C Total Points /30 /12 /12 /6 /10 /10 /20
School: University Of Michigan
Course: Circuits
Sample solutions EECS 314 Winter 2008 Final Exam Instructor: Alexander Ganago ganago@umich.edu Wednesday April 23, 2008, 10:30 AM 12:30 PM Exam rooms, according to the [first letter of] students' last names: A.K L.P R.Z 220 Chrysler Auditorium (our lectur
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
uniqname: _ EECS 280 Final Exam Fall 2012 This is a closed-book exam. There are 5 problems on 17 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that i
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS 280: Midterm Fall 2006 This is a closed-book exam; no notes are allowed. There are 5 problems on 17 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note al
School: University Of Michigan
EECS 216 EXAM #2 - Winter 2008 x(t) cos(3t)dt=: 1. Fourier series of x(t) is cos(t)+ 1 cos(2t)+ 1 cos(3t)+. . . Then 2 3 1 (a) 0 (b) 3 (c) (d) (e) 2 6 3 3 2 2. Impulse response of an LTI system with frequency response (j)2 +4(j)+4 is: (a) Nonc
School: University Of Michigan
Course: Programming And Data Structures
EECS 280: Midterm Winter 2012 This is a closed-book exam. There are 5 problems on 13 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that is required o
School: University Of Michigan
Course: Programming And Data Structures
uniqname: EECS 280 Midterm Exam Spring 2012 This is a closed-book exam. There are 5 problems on 13 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS 280: Final Fall 2006 This is a closed-book exam; no notes are allowed. There are 5 problems on 13 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all
School: University Of Michigan
Course: PROBABILITY
EECS 501 Quiz 1, Mo 2:30-4:00 Problem 1 A Person is asked to assign probabilities to the following events: E1 : Trump wins Iowa primary, E2 : Trump wins New Hampshire primary, E3 : Trump wins both Iowa and New Hampshire primaries, and E4 : Trump wins none
School: University Of Michigan
Course: PROBABILITY
EECS 501 Quiz 1, Mo 4:30-6:00 Problem 1 Prove the union bound for three events. P (A B C) P (A) + P (B) + P (C) Solution: From HW: P (A B C) = P (A) + P (B) + P (C) P (A B) P (A C) P (B C) + P (A B C) But A B C A B so P (B C) + P (A B C) 0, Also P (A C) P
School: University Of Michigan
EECS 451 FALL 2014 HW 8 DUE DECEMBER 2 After a genuine attempt to solve the homework problems by yourself, you are free to collaborate with your fellow students to nd solutions to the homework problems. Regardless of whether you collaborate with other 451
School: University Of Michigan
School: University Of Michigan
School: University Of Michigan
EECS 280: Final Winter 2010 This is a closed-book exam. There are 5 problems on 15 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that is required of
School: University Of Michigan
EECS 280: Final Winter 2011 This is a closed-book exam. There are 5 problems on 15 pages. Read the entire exam through before you begin working. Work on those problems you find easiest first. Read each question carefully, and note all that is required of
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ EECS370MidtermExam Winter2015 Thisisaclosed bookexam.Youmayuseonenotesheet,8.5x11,double sided.Thisexam has10problemson16pages.Calculatorsarepermitted,butwirelessdevicesarenot. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsy
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ EECS370MidtermExam Winter2015 Thisisaclosed bookexam.Youmayuseonenotesheet,8.5x11,double sided.Thisexam has_problemson16pages.Calculatorsarepermitted,butwirelessdevicesarenot. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsyo
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
EECS370MidtermExamTopics Thefollowingtopicsareeverythingwhichhasbeencovereduptothispointinlectureand couldpotentiallyshowupontheMidtermexam.Somemaynotappearduetoexamtime constraints.Inpastsemesters,thecoursewasrunslightlydifferently.Ifyouseeaquestion outs
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ _ EECS370MidtermExam Fall2014 Thisisaclosed bookexam.Youmayuseonecheatsheet,8.5x11,double sided.Thisexam has6problemson13pages.Noelectronicsorcalculators. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsyoufind easiestfirst.Re
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ _ EECS370MidtermExam Fall2014SOLUTION Thisisaclosed bookexam.Youmayuseonecheatsheet,8.5x11,double sided.This examhas6problemson14pages.Noelectronicsorcalculators. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsyoufind easiest
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ _ EECS370FinalExam Fall2014 Thisisaclosed bookexam.Youmayuseonecheatsheet,8.5x11,double sided.This examhas7problemson15pages.Noelectronicsorcalculators. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsyoufind easiestfirst.Read
School: University Of Michigan
Course: INTRODUCTION TO COMPUTER ORGANIZATION
uniqname:_ _ EECS370FinalExamFall 2014SOLUTION Thisisaclosed bookexam.Youmayuseonecheatsheet,8.5x11,double sided.This examhas7problemson15pages.Noelectronicsorcalculators. Readtheentireexamthroughbeforeyoubeginworking.Workonthoseproblemsyoufind easiestfi
School: University Of Michigan
Course: Data Structures And Algorithms
The University of Michigan Electrical Engineering & Computer Science EECS 281: Data Structures and Algorithms Winter 2015 M IDTERM E XAM , PRACTICE Wednesday February 25, 2015 7:10PM 8:40PM (90 minutes) Name: Uniqname: Student ID: Discussion section: (cir
School: University Of Michigan
Course: Data Structures And Algorithms
The University of Michigan Electrical Engineering & Computer Science EECS 281: Data Structures and Algorithms Winter 2015 M IDTERM E XAM , PRACTICE Wednesday February 25, 2015 7:10PM 8:40PM (90 minutes) Name: Uniqname: Student ID: Discussion section: (cir
School: University Of Michigan
Course: Data Structures And Algorithms
EECS 281 Final Exam Sample Questions For each of the following tasks, fill in the best, worst, and average case complexity. For a given task, assume you use the same algorithm for all three cases, and that there are already n items in the data structure.
School: University Of Michigan
Course: Data Structures And Algorithms
EECS 281 Final Exam Sample Questions For each of the following tasks, fill in the best, worst, and average case complexity. For a given task, assume you use the same algorithm for all three cases, and that there are already n items in the data structure.
School: University Of Michigan
Course: Database Mgt Syst
EECS 484: Final Exam, Winter 2013 Please print your name and uniqname below. Name: Uniqname: Instructions: 1. The total number of points on this exam is 105. 2. During the exam, you may use three sheets of notes (stapled and with your names on each sheet)
School: University Of Michigan
Course: DISCRETE MATHEMATICS
Sample Exam 2 EECS 203 Spring 2014 You have two hours to complete this exam. You may use any information you have written on two 8.5 11 sheets of paper. Problem 1. Zero or more of the following statements are true. Which ones are they? (a) The number of p
School: University Of Michigan
Course: DISCRETE MATHEMATICS
Sample Exam 1 Answers EECS 203 Spring 2014 Each part of Problem 1-9 is a true-false question. Here are the answers Problem 1 2 3 4 5 Part Answer a F b T c T d F a T b F c T d T a F b F c F d T a T b F c T d F e T a T b T c T d F Problem Part Answer 6 a T
School: University Of Michigan
Course: Digital Integrated Technology
H N % -L qj _\ Q q - - 4-ED c ) c) - L \ Hj c N ( s .& I o >< <.-.-. - . . , - I c It N l cA -1 i 1 Q c 0 aI <1 1- + 1 ; - r 0 a LA I a o. _ -p -t 1 k >( 0 )S + I N - P. ft I - r4\ (r\ p co> IoI. [ *7 ts 7oxc ) O/Q 4 / s+ SvI/yjf tJ5ij fi /),o6/e4- 2 1OS
School: University Of Michigan
Course: Digital Integrated Technology
) /-ik/f3 4- e Fa piu + e/A, sI p & II14 4/oi11 = I /-/Dq.2JAi 492q + i,t 1 A1 ,ww I (i&17q s)?Ivf I Q Z.4 ,c, C4c 3E) ,/ to -c )Y(.)L1)acO/ itl :d J(I UVfJ1141 1 . .4 I). ,OL4nDAC ,p,q do . 1 , af2L1P( [7 ,tQO U! :LA ft?1 c91 t) i 1 h e*Z 1 L, fa4L1qUI4
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 551/453 - HOMEWORK 1 Reading pertaining to the problem set: Chapter 1 of Laub Reading for next week: Chapter 2 Section 9.1 of Laub Problems marked with an asterisk (*) are for EECS 453 *Problem 1. Express the n m matrix A whose j th row equals j as a
School: University Of Michigan
Course: Math Meth Sig Proc
EECS551: HW2 SOLUTIONS Problem 1 T Let A = QQ be the eigendecomposition of A. Then we may write B = A 10I = QQT 10QQT (I = QQT since Q is orthogonal) = Q( 10I)QT (0.1) Notice that 10I is a diagonal matrix, and since Q is orthogonal, the right hand side of
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW 3 Reading for next week: Chapter 2 and Chapter 3 of Laub EECS 551 students solve all problems. EECS 453 students only solve problems with a *. *Problem 1. This what is known about the dietary habits of the mythical Michigan Wolverine who
School: University Of Michigan
Course: DISCRETE MATHEMATICS
EECS 203: DISCRETE MATHEMATICS Homework 9 Solutions 1. (9 points) If R V V is a binary relation over V then R1 (the inverse) is dened as: (x, y ) R if and only if (y, x) R1 . Prove or disprove the following: (a) If R is transitive & reexive then R R1 is a
School: University Of Michigan
Course: Database Mgt Syst
EECS 484 Homework #5 Question 1 Consider the following relational schema and SQL query: Students(sid, sname, gpa) Takes(sid, cid) Class(cid, cname, ctype) SELECT S.sname, C.cname FROM Students S, Takes T, Class C WHERE S.sid = T.sid AND T.cid = C.cid AND
School: University Of Michigan
Course: ML
EECS445: Introduction to Machine Learning, Fall 2014 Homework #1 Due date: 5pm on 9/23 (Tuesday) Reminder: While you are encouraged to think about problems in small groups, all written solutions must be independently generated. Please type or hand-write s
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW1 SOLUTIONS Problem 1 (*) m Let e R be a vector with ei = 1 for i = 1, . . . , m. Let x Rn be a vector with xj = j for j = 1, . . . , n. Then the desired n m matrix whose j-th row equals j is given by the outer-product xeT . In MATLAB we w
School: University Of Michigan
Course: Computer Vision
EECS 442 Computer Vision, Homework 2 Due on , Please submit your assignment on ctools 1 [30 points] Fundamental Matrix In this question, you will explore some properties of fundamental matrix and derive a minimal parameterization for it. (a) [10 points] S
School: University Of Michigan
Course: Database Mgt Syst
EECS 484 Homework #5 Question 1 Consider the following relational schema and SQL query: Students(sid, sname, gpa) Takes(sid, cid) Class(cid, cname, ctype) SELECT S.sname, C.cname FROM Students S, Takes T, Class C WHERE S.sid = T.sid AND T.cid = C.cid AND
School: University Of Michigan
Course: Digital Integrated Technology
University of Michigan Department of Electrical Engineering and Computer Science EECS 523 HW#4 Fall 2012 Due (at the beginning of the class): October 30 1- A 0.5m thin poly has been implanted with both phosphorus and boron impurities with a dose of 6 x 10
School: University Of Michigan
Course: Data Structures And Algorithms
UniversityofMichigan EECS281:DataStructuresandAlgorithms Homework1 Fall2015 Assigned : TuesdaySep15,2015,11:59PM Due : ThursdaySep24,201511:59PM Instructions : Homework1isworth25totalpoints.EnteryourresponsestoProblems 14ontheCToolsTestCenter.Problem5must
School: University Of Michigan
Course: Introduction To MEMS
EECS 414 Introduction to MEMS Homework #3 Total: 180 Points Fall 2007 Handed Out: Due: Friday Sept. 21, 2007 Friday Sept. 28, 2007 1. This problem deals with etching of the silicon device shown below. The figure shows the cross section and the t
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW3 SOLUTIONS Problem 1 (*) The transition probability matrix is Cheese 0 1/2 1/2 Cheese P = Grapes Lettuce Grapes 4/10 1/10 5/10 Lettuce 6/10 4/10 0 T Let = 1 2 3 be the equilibrium distribution of the states (Cheese, Grapes, Lettuce),
School: University Of Michigan
EECS 314 Winter 2008 Homework set 8 Student's name _ Discussion section # _ (Last, First, write legibly, use ink) (use ink) Instructor is not responsible for grading and entering scores for HW papers lacking clear information in the required field
School: University Of Michigan
EECS 203, Discrete Mathematics Winter 2007, University of Michigan, Ann Arbor Problem Set 5 Problems from the Textbook 9.1: 24[E] 9.2: 58[M] 9.3: 32[M], 68[M] 9.4: 16[E] 2.4: 26[C], 38[E] * Additional Problems Required for All Students Problem A5.
School: University Of Michigan
EECS 203: Homework 1 Solutions Section 1.1 1. (E) 8bef b) You do not miss the final exam if and only if you pass the course. e) If you have the flu then you do not pass the course, or if you miss the final examination then you do not pass the course. f) Y
School: University Of Michigan
Course: Comp Architec
EECS 470 Fall 2014 HW1 solutions 1a) Loop: LD DADDI SD DADDI DSUB DADDI BNEZ R1, 0(R2) R1, R1, #1 0(R2), R1 R2, R2, #4 R4, R3, R2 R5, R5, #1 R4, Loop Instruction 1 2 3 4 5 LD IF ID EX MEM WB IF ID* ID* IF* IF* 8 ID EX MEM WB IF ID* ID* IF* 10 11 ID EX MEM
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551 - HW 2 Reading pertaining to problem set: Chapter 2, Chapter 5.1, Chapter 9.1, Chapter 13.1-13.2 Reading for next week: Chapter 3, Chapter 5.2 EECS 551 students solve all problems. EECS 453 students solve ONLY the problems that are NOT marked
School: University Of Michigan
Course: : Introduction To Artificial Intelligence
EECS 492 Fall 2012 Homework 6 Solution Guide 1. adult.data.ar @RELATION adultdata @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE @ATTRIBUTE age NUMERIC workcla
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: HW 10 SOLUTIONS Problem 1 (*) Dene the diagonal matrix n = diag(n1 , n2 , . . . , 1) so that we can denote We need to minimize: n1 n2 n = diag( , , . . . , 1). | n (yn xn h)|2 T where yn = y(n) y(n 1) . . . minimizing: T and xn = x(n) x(n
School: University Of Michigan
Course: Embedded Control Systems
EECS 461, Spring 2014, Problem Set 71 issued: June 12, 2014 due: June 19, 2014 To receive full credit for your answers to the following questions, please explain your reasoning carefully. 1. In the following code, the function lSecondsSinceMidnight return
School: University Of Michigan
Course: Introduction To MEMS
EECS 414 Introduction to MEMS Reading Assignments Fall 2007 Class Handouts and Notes, Bulk Micromachining, Surface Micromachining, and Wafer Bonding. Homework #5 Total: 240 Points Handed Out: Friday October 5, 2007 Due: Friday October 12, 2007 1.
School: University Of Michigan
Course: Introduction To MEMS
EECS 414 Introduction to MEMS Reading Assignments Homework #2 Total: 165 Points Fall 2007 Class Handouts and Notes, Introduction to Microfabrication Technologies Handed Out: Due: Thursday Sept. 13, 2007 Friday Sept. 21, 2007 1. Thermal and e-b
School: University Of Michigan
Course: Computer Vision
EECS 442 Computer Vision, Fall 2012 Homework 1 Solution Problem 1 (a) To construc the rotation matrix R, we write the cooridantes of the basis vectors of W in terms of those of C so that any point in W coordinates can be transformed into C coordinates. 2
School: University Of Michigan
Problem 1.6 A certain cross section lies in the xy plane. If 3 1020 electrons go through the cross section in the z-direction in 4 seconds, and simultaneously, 1.5 1020 protons go through the same cross section in the negative z-direction, what is the mag
School: University Of Michigan
Course: Dsp Design Lab
EECS452 Homework#2 Mei Yang 1. Answer: a. 35(dec) = 4*8 + 3 = 43 (oct) b. 35(dec) = 2*16 + 3 = 23 (hex) c. 1111_1111(2s complement) = 1 (dec) d. 1000_1000(2s complement, Q4) = 8+0.5=7.5 e. 1111_1111(binary u
School: University Of Michigan
Course: Circuits
EECS314 Studentsname_ Discussionsection#_ (Last,First,writelegibly,useink) (useink) InstructorisnotresponsibleforgradingandenteringscoresforHWpaperslacking clearinformationintherequiredfieldsabove Winter2011 Homeworkset3 Problem1(20points)Resistanceandr
School: University Of Michigan
EECS 203 HW 1 10. Let p, q, and r be the propositions p: You get an A on the final exam. q: You do every exercise in this book. r: You get an A in this class. Write these propositions using p, q, and r and logical connectives. a) You get an A in this
School: University Of Michigan
Course: Dsp Design Lab
EECS452 Lab4 Pre-lab Mei Yang Q1. Answer: From the figure that has been generated, we can clearly see that the max gain is 60dB. Q2. Answer: From the matlab design, we can easily get that: a. 210 b. 35 Q3. Answer: For the passband, the difference is very
School: University Of Michigan
Course: Embedded Control Systems
EECS 461 Spring 2014 Lab 1: Familiarization and Digital I/O 1 Overview The purpose of this lab is to familiarize you with the hardware and software used in EECS 461. For this class we will be using a 32-bit oating-point Freescale MPC5553 microcontroller r
School: University Of Michigan
Course: Dsp Design Lab
Pre-lab questions: Q1. Consider the logic statement (A*B)+(C*A) a. Write the truth table for that logic statement b. Draw the gates that implement that logic statement (without simplification). A, B 00 01 10 11 C=0 0 0 0 1 C=1 1 1 0 1 Q2. Consider a 2-to-
School: University Of Michigan
EECS 215 Lab Supplementary Materials / Op Amp Lab Cover page Op Amp Lab Report Students Name _ Date of Lab Work _ I have neither given nor received aid on this report, nor have I concealed any violations of the Honor Code. _ (students signature) Lab Secti
School: University Of Michigan
Course: Parallel Computing
Serial Quicksort Quicksort is an important sorting algorithm. Given an array A(1:n) of items to be sorted, Quicksort(i,j,A) sorts the items in positions i . . . j. To sort the entire array, the main program calls Quicksort(1,n,A). Quicksort(i,j,A): If j
School: University Of Michigan
EECS 551/EECS 453 EIG/SVD & what you can do with it 1. Sensor localization Multidimensional scaling http:/www.mathworks.com/products/statistics/demos.html?file=/products/demos/shipping/stats/cmdscaledemo.html MATLABs cmdscale.m Cmdscale.m 2. Image Compre
School: University Of Michigan
vm_create (6028) vm_switch (6028) returning to (6028) with pages: vm_extend (6028) 1 vm_extend returned 0x60000000 returning to (6028) with pages: vm_extend (6028) 2 vm_extend returned 0x60001000 returning to (6028) with pages: vm_extend (6028) 3 vm_exten
School: University Of Michigan
UCSD4& UCSDCU La Scala La ScalaLa Scala Luxury Villas201 10 Scala La apartment house 3 * 20134
School: University Of Michigan
Contents Text Features ix Preface xi 1 Linear Equations 1.1 1.2 1.3 2 Linear Transformations 2.1 2.2 2.3 2.4 3 Introduction to Linear Systems Matrices, Vectors, and Gauss-Jordan Elimination On the Solutions of Linear Systems; Matrix Algebra Introduction t
School: University Of Michigan
CAEN Remote Access * CAEN Accounts CAEN accounts are REQUIRED for EECS 281 http:/caen.engin.umich.edu/hotline * Connect to CAEN Remote CAEN VNC (Linux) http:/caen.engin.umich.edu/connect/vnc SFTP Transfer from your local machine http:/caen.engin.umich.edu
School: University Of Michigan
EECS281 Discussion 1 Welcome to Discussion! What happens in discussion? Practice problems (exams/hw) Project specifications Class Logistics Programming exercises Interview style problems Agenda This week: Makefiles C+11 Getopt I/O Makefiles Makefiles are
School: University Of Michigan
Course: Digital Integrated Circuits
Lab 1: Introduction to Cadence EECS 312 Fall 2015 Posted: Thursday September 10, 2015 Due: Friday October 2, 2015, beginning of Discussion 1. Introduction This tutorial has been devised to walk you through all the steps involved in the design and simulati
School: University Of Michigan
Course: Data Structures And Algorithms
Project 1: The STL and You A quick intro to the STL to give you tools to get started with stacks and queues, without writing your own! Use a deque instead! Speed up your output! The vector<> Template You must #include <vector> Basically a variable-sized a
School: University Of Michigan
Course: Data Structures And Algorithms
EECS281Fall2015 ProgrammingAssignment1 SinisterSorceryandStacks (PathFinding) DueTuesday,September2911:55PM Overview BlimeyEvilLordMoldywarthasthreatenedtotakeoverthewizardingworld!Ouronlychance ofsurvivalisforPerryHotter,theChosenOne,tofindthemagicringin
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 07: ADTs and Polymorphism Due Friday, 31 October 2014, 11:55pm Inthislab,wewillrefactorandbuildontotheASCIIartprogramwefirstsawinLab4.Wewill useasetofAbstractDataTypes(ADTs)towritetheprogram
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
QuickReferences EECS 280 Lab 10: The Big Three Due Friday, 21 November 2014, 11:55pm Unfortunately,itturnsoutourA r y n V c o fromthepreviouslabstillhasafewissues raItetr thatcanleadtomemoryerrors.Whenweswitchedtousingadynamicallyallocatedarray, weprovide
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS 280 Lab 12: Functors (Not Collected) Inthislab,youwilllearnhowtodefineandusefunctors.Functorsaresimilartofunction pointers,butmuchmorepowerful.Theycancontainstateandtheybehavejustanyother objectinyourprogram!Indeed,aFunctorisanobjectwhichactslikeafu
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
QuickReferences EECS 280 Lab 11: Iterators Due Friday, 5 December 2014, 11:55pm Inthislab,wewillpracticeusingSTLstyleiteratorsforthesinglylinkedListclassintroduced inlecture.We'lluseValgrindtomakesurewecleanupmemorycorrectly. Thislabcoversmaterialfromthes
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 09: Dynamic Memory Due Friday, 14 November 2014, 11:55pm Inthislab,wewillmodifyI t e t r n V c o fromthepreviouslabbyusingdynamicallyallocated arraystosupportstorageofarbitrarilymanyelements
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 08: Container ADTs Due Friday, 7 November 2014, 11:55pm Inthislab,wewillpracticecreatingandusingcontainerabstractdatatypes.Acontainerisan objectthatcanstoreacollectionofelements.Inthisexampl
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 06: Structs and Classes Due Friday, 24 October 2014, 11:55pm Inthislab,youwillpracticetechniquesforobjectorientedprogramming.We'lljuxtaposeboththe Cstyle(structs)andtheC+style(classes)herein
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
QuickReferences EECS 280 Lab 05: Strings and IO Due Friday, 10 October 2014, 11:55pm Inthislab,youwillpracticestringmanipulation(usingbothCstringsands r n objectsfrom tig theC+StandardLibrary)andfileinput/outputinC/C+andusethemtoimplementasimple spellchec
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
QuickReferences EECS 280 Lab 04: Arrays and Pointers Due Friday, 3 October 2014, 11:55pm Inthislab,youwillreviewthebasicsofpointersinC/C+andpracticeusingthemtotraverse andmanipulatearrays.Ourmotivatingexamplewillbethedesignofacanvasthatprintsout simpleASC
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 03: Function Pointers Due Friday, 26 September 2014, 11:55pm Inthislab,youwillpracticedefiningandusingfunctionpointers,inparticulartoimplementhigher orderfunctions.Alongtheway,we'llalsotakea
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 01: Linux Due Friday, 12 September 2014, 11:55pm Inthislab,youwillconnecttoCAENLinuxandusebasicLinuxcommandstonavigatefilesand directories,andtowrite,compile,run,andtestasimpleprogram.Youwil
School: University Of Michigan
Course: PROGRAMMING AND INTRODUCTORY DATA STRUCTURE
EECS280F14GoogleDriveRepository http:/goo.gl/GWEL82 EECS 280 Lab 02: Recursion Due Friday, 19 September 2014, 11:55pm Inthislab,youwillwritefunctionsusingiteration(loops),recursionandtailrecursion.You'llalso learnhowtousetheEECS280Labsterprogramvisualizat
School: University Of Michigan
Lab 3: Feedback Control Professor Kim Winick (Adapted by Dianguang Ma) PreLab 3.1 Plant In this laboratory experiment we have decided to construct our own plant so that we will know its characteristics. The plant circuit is shown in Fig. 3.1.1. 3.1.1 Usin
School: University Of Michigan
Course: Computer Architecture
EECS 470 Lab 5 Linux Shell Scripting Department of Electrical Engineering and Computer Science College of Engineering University of Michigan Friday, 5th February, 2015 (University of Michigan) Lab 5: Scripting Friday, 5th February, 2015 1 / 40 Overview Ad
School: University Of Michigan
Course: Computer Architecture
EECS 470 Term Project Winter 15 The term project is to build on the VeriSimple4 Alpha pipeline to create a more advanced pipeline with a few of the features we are studying in class. Projects will be done in groups of four or five students (with 5 being p
School: University Of Michigan
EECS 373 Lab 3: Introduction to Memory Mapped I/O In this lab we will learn: To develop custom peripheral hardware in the SmartFusion FPGA using the Libero CAD tools. The fundamentals of memory-mapped I/O (MMIO). To interface the ARM peripheral bus (APB3)
School: University Of Michigan
Course: PROBABILITY
Chapter 1 Sigma-Algebras 1.1 Denition Consider a set X . A algebra F of subsets of X is a collection F of subsets of X satisfying the following conditions: (a) F (b) if B F then its complement B c is also in F (c) if B1 , B2 , . is a countable collection
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 453/551: Googles Page-Rank algorithm In MATLAB, load the eecs.umich.edu adjacency matrix you produced by running surfer.m. Please download the pagerank_demo.zip file from Canvas under files\demos\pagerank section and unzip it into a working folder. I
School: University Of Michigan
Course: Math Meth Sig Proc
Thursday, September 18, 2014 1:27 PM Discussion Week 3 Page 1 Thursday, September 18, 2014 1:40 PM Discussion Week 3 Page 2 Thursday, September 18, 2014 1:45 PM Discussion Week 3 Page 3 Thursday, September 18, 2014 1:55 PM Discussion Week 3 Page 4 Thursda
School: University Of Michigan
Course: Math Meth Sig Proc
Discussion 2 Follow Up David Hiskens September 21, 2015 Eigendecomposition of Non-Diagonal Matrix There was a request for an example of an eigendecomposition in which the eigenvectors were not trivially the columns of the identity matrix. Consider the fol
School: University Of Michigan
Course: Comp. Vision
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. PAMI-8, NO. 6, NOVEMBER 1986 679 A Computational Approach to Edge Detection JOHN CANNY, MEMBER, IEEE Abstract-This paper describes a computational approach to edge detection. The success
School: University Of Michigan
Course: Comp. Vision
An Introduction to Projective Geometry for computer vision Stan Birch eld 1 Introduction We are all familiar with Euclidean geometry and with the fact that it describes our threedimensional world so well. In Euclidean geometry, the sides of objects have l
School: University Of Michigan
Course: PROBABILITY
EECS 501- Discussion 3 Discrete Random Variable Important Discrete PMFs: Bernoulli Random Variable: |S| = 2, X(S) = cfw_0, 1, P (1) : = p, p cfw_0, 1, E(X) = p, V ar(X) = p(1 p) Example: Tossing a coin, Passing a test Binomial: |S| = N + 1, N N cfw_0, X
School: University Of Michigan
Course: PROBABILITY
University of Michigan FALL 2015 Random Variable Consider a random experiment with sample space and an event space (sigma-algebra) F. Let P be a probability measure on F. We say that (, F, P ) is a probability space. We study the concept of random variabl
School: University Of Michigan
Course: Parallel Computing
Standard Computer Science Notation and Mathematics c Quentin F. Stout lg ln n! n m x x log base 2 Remember that loga x = loga b logb x. log base e n factorial, i.e., n (n 1) . . . 2 1. n choose m, the number of distinct subsets of m items in a set of n di
School: University Of Michigan
Course: Embedded Control Systems
Matlab RC Filter Design % m-file generates an R-C circuit antialiasing filter num = 1; den = [RC 1]; omega = logspace(-1,3); [mag, phase] = bode(num, den, omega); subplot(2,1,1) % Magnitude and Phase on one page % plot magnitude in dB vs. frequency in Hz
School: University Of Michigan
Course: Embedded Control Systems
EECS 461: Final Project Work Breakdown (Sp14) Work may be completed in any order or at a pace faster than listed below. Below is a suggestion which will allow you to complete as much modeling as possible outside of lab. However, you are responsible for ha
School: University Of Michigan
Course: Embedded Control Systems
RAppID Reference EECS461 March 28, 2013 1 GPIO Peripheral Blocks The main functionality of the GPI block is to set the selected GPIO pin for general purpose input. All the available pins are connected to Dipswitches in the lab. The main functionality of t
School: University Of Michigan
Course: Intr Art Intell
syllabus-F15.xlsx 9/4/15 EECS 492: Artificial Intelligence topic read before class 9/8 9/10 What is AI? Agents and environments chapter 1 (29p) chapter 2 (22p) 9/15 9/17 State spaces and search Beyond classical search chapter 3 (45p) chapter 4 (34p) 9/22
School: University Of Michigan
Course: Intr Art Intell
EECS 492: Introduction to Artificial Intelligence Fundamental concepts of AI, organized around the task of building computational agents. Core topics include search, logic, representation and reasoning, automated planning, representation and decision maki
School: University Of Michigan
Course: Comp. Vision
EECS 598-01 Special Topic Foundations of Computer Vision Fall 2015 MW 12:00-1:30PM in 1005 DOW Course Overview: Computer Vision seeks to extract useful information from images, video and other visual content. This course will introduce the breadth of mode
School: University Of Michigan
Course: Comp. Vision
EECS 598-01 Foundations of Computer Vision Electrical Engineering and Computer Science University of Michigan Syllabus for Fall 2015 Last updated: 8 September 2015 Instructor: Jason Corso (jjcorso) Course Webpage: http:/web.eecs.umich.edu/jjcorso/t/598F15
School: University Of Michigan
Course: Comp. Vision
Week Monday Wednesday 9/7 No Class: Before Term 1: Introduction 9/14 2: Images as Functions 3: Image Operations 9/21 4: Geometric Invariance 5: Case Study on Geometric Invariance by Local Features: Rotation Invariance 9/28 6: Case Study on Geometric Invar
School: University Of Michigan
Course: Parallel Computing
Parallel Computing: EECS 587 Quentin F. Stout 3605 CSE 763-1518 qstout@umich.edu www.eecs.umich.edu/~qstout Texts: None, but some computer manuals will be used, and there will be various papers, book excerpts, and web resources. Course Overview: The cours
School: University Of Michigan
Course: DISCRETE MATHEMATICS
EECS 203, F12 syllabus Lec Day Date Topic Logic, Proofs, and Objects (sets, relations, functions) 1 Tue 4-Sep-12 Introduction to Course, Propositional Logic 2 Thu 6-Sep-12 Propositional Equivalences 3 Tue 11-Sep-12 Predicates and Quantifiers
School: University Of Michigan
ME564/EE560/AERO550/CEE571 - Linear Systems Theory Univ. of Michigan, Fall 2015 Instructor: Prof. Brent Gillespie 2142 GG Brown 647-6907 email: brentg@umich.edu Lectures: Oce Hours: Mo,We,Fr 1:30-2:30, 1670 Beyster see ctools homepage GSIs: Justin Storms,
School: University Of Michigan
EECS 551: MATRIX METHODS FOR SIGNAL PROCESSING, DATA ANALYSIS & MACHINE LEARNING EECS 453: APPLIED MATRIX ALGORITHMS FOR SIGNAL PROCESSING, DATA ANALYSIS & MACHINE LEARNING Summary: Theory and application of matrix methods to signal processing, data analy
School: University Of Michigan
Course: PROBABILITY
EECS 501: Probability and Random Processes University of Michigan, Fall 2015 Section 1 Lectures: Tu Th 10.30-12.00 AM, (BEYSTER 1670) Instructor: S. Sandeep Pradhan Email: pradhanv@umich.edu Office: 4240 EECS Office hours: W 3-5 PM (EECS 2246), Fri 3-4 PM
School: University Of Michigan
Course: PROBABILITY
EECS 501: Detailed Syllabus University of Michigan, Fall 2015 1. Sep 8, Course logistics, Set operations, Event space 2. Sep 10, Probability measure, conditional probability, independence 3. Sep 15, Law of total probability, Bayes' rule, MAP rule, sequ
School: University Of Michigan
Course: Math Meth Sig Proc
EECS 551: MATRIX METHODS FOR SIGNAL PROCESSING, DATA ANALYSIS & MACHINE LEARNING EECS 453: APPLIED MATRIX ALGORITHMS FOR SIGNAL PROCESSING, DATA ANALYSIS & MACHINE LEARNING Summary: Theory and application of matrix methods to signal processing, data analy
School: University Of Michigan
Course: Intr Art Intell
EECS 492: Introduction to Artificial Intelligence Fall 2014 Instructor: Prof. Emily Mower Provost Office Hours: Wednesday 911 Office: 3620 CSE emilykmp@umich.edu GSIs: GSI office hours will take place in the EECS Learning Center (BBB 1637). Duc Le Office
School: University Of Michigan
Course: Computer Vision
EECS442ComputerVision CourseDescription Thecourseisanintroductionto2Dand3Dcomputervision.Topicsinclude:camerasmodels,the geometryofmultipleviews;shapereconstructionmethodsfromvisualcues:stereo,shading,shadows, contours;lowlevelimageprocessingmethodologies
School: University Of Michigan
Course: Linear Systems Theory
No textbook is required. The following book is RECOMMENDED (but once again, not required). It is on reserve in the library. 1) ISBN: 9780471735557 Linear State-Space Control Systems Robert L Williams, III, Douglas A Lawrence The following books are also o
School: University Of Michigan
Course: Linear Systems Theory
EECS 560: LINEAR SYSTEMS THEORY OR (LINEAR ALGEBRA FOR FUN AND PROFIT) Instructor: Prof. Jessy W. Grizzle, 4421 EECS Bldg., grizzle@umich.edu, 734-7633598 Class Periods: Lecture meets MWF, 1:30 to 2:30 PM in 1670 CSE Fldg. Recitation meets W 4:30 to 6:30
School: University Of Michigan
Course: Lin Feedback Control
EECS 565: Linear Feedback Control Systems, Winter 2011 TIME: 10:30-12:00 Tuesday and Thursday PLACE: 1303 EECS Bldg. INSTRUCTOR: J. S. Freudenberg OFFICE: 4425 EECS bldg PHONE: (734) 763-0586 EMAIL: jfr@eecs.umich.edu OFFICE HOURS: 2:00-3:00 Monday and 12
School: University Of Michigan
Course: Introduction To Cryptography
University of Michigan, Computer Science and Engineering EECS 475: Introduction to Cryptography Instructor: Prof. Kevin Fu Handout 1 January 8, 2014 Course Information Instructor: Prof. Kevin Fu Lecture: Mondays/Wednesdays 10:30-12:00 (1610 IOE) Oce Hours
School: University Of Michigan
Course: Introduction To Machine Learning
ECE-340 Spring 2008 Probabilistic Methods in Engineering (3 credits) M, W 3:00-4:15 PM Room: Dane Smith Hall 325 Syllabus Course Goals: To introduce the student to basic theoretical concepts and computational tools in probability and statistics with empha
School: University Of Michigan
Course: Introduction To Probability
ECE-340 Spring 2008 Probabilistic Methods in Engineering (3 credits) M, W 3:00-4:15 PM Room: Dane Smith Hall 325 Syllabus Course Goals: To introduce the student to basic theoretical concepts and computational tools in probability and statistics with empha
School: University Of Michigan
Stats 412: Introduction to Probability and Statistics Winter 2013 Instructor: Dr. Shyamala Nagaraj 270 West Hall, 734-764-5493, shyamnk@umich.edu Section 1: T Th Lecture hours: 10 - 11.30 a.m., 296 Dennison GSI: Zahra Razaee, razaee@umich.edu Exam 1: Thur
School: University Of Michigan
EECS 482: Introduction to Operating Systems Winter 2013 1 Basic information Lecture time & place: TTh 4:30-6pm, 1013 Dow Instructor: Jason Flinn, jflinn@umich.edu, office hours M 2:30-4:30pm, 4641 BBB Course staff: Nathaniel Daly, Brett Higgins, Justin Pa
School: University Of Michigan
Rev 1/26/2013 Page 1 of 3 Syllabus CSE 496 Winter 2013 Instructor, Elliot Soloway, Instructor, soloway@umich.edu GSI, Prateek Tandon, prateekt@umich.edu YOU MUST JOIN THIS EMAIL LIST: 1. Go to: directory.um
School: University Of Michigan
Course: Linear Systems Theory
Syllabus ME 564/EECS 560/Aero 550 Prof. Tilbury, UMich, Fall 2012 Lectures: MWF 1:302:30pm, 1670 Beyster Instructor: Prof. Dawn Tilbury, 3124 GG Brown, 936-2129, tilbury@umich.edu. Ofce Hours: MWF 2:30-3:30pm or by appointment GSIs: Hamid Ossareh, hamido@
School: University Of Michigan
Course: Power Electronics
Syllabus for EECS 418 Power Electronics Fall 2012 Pre-requisites: EECS 215 and EECS 216, and preceded or accompanied by EECS 320, or graduate standing. Course: Lecture: Lab, Section 1: Lab, Section 2: Lab, Section 3: MW 3:00 p.m.4:30 p.m., Th 3:00 p.m.6:0
School: University Of Michigan
Course: PROBABILITY
EECS 501 Probability and Random Processes Fall 2009 Lectures: TTh 10:30 am 12 noon, 1500 EECS Bldg. Recitation: Tue 3:30 pm 5 pm 1010 DOW Bldg. (section 11) or M 4:30 pm -6 pm, 2233 GGBL Bldg. (section 12) Instr uctor: Professor K. A. Winick 4423 EECS Bld
School: University Of Michigan
EECS 215: Introduction to Electronic Circuits Winter Semester 2010 Instructors: Section 1: 9:30-10:30 AM, MWF and 1:30-2:30 PM, F, Prof. Fred Terry 2417F EECS Bldg. fredty@umich.edu (Please include EECS215 in the subject line) 763-9764 Section 2: 1:30-2:3
School: University Of Michigan
Course: Embedded Control
EECS 461: Embedded Control Systems, Winter 2009 CLASS TIME: 1:303:00 Monday and Wednesday LAB TIMES: Monday, 3:306:30; Tuesday, 1:304:30; Wednesday, 10:001:00; Thursday, 9:3012:30; Thursday, 1:304:30 PLACE: 1311 EECS (lecture), 4342 EECS Building (l
School: University Of Michigan
EECS 523 DIGITIAL INTEGRATED CIRCUIT TECHNOLOGY COURSE SYLLABUS WINTER 2007 The following comprises a tentative syllabus describing the material to be covered in the course EECS 523, Digital Integrated Circuit Technology, for Winter 2007. Material
School: University Of Michigan
Course: Intro Oper System
EECS 482: Introduction to Operating Systems Winter 2006 1 Basic Information Prof. Atul Prakash, 4741 CSE, aprakash@eecs.umich.edu Graduate Student Instructors Mark Hodges (Monday discussions) Paul Darga (Friday discussions). Web page: http:/www.ee