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Ldpc_225c
School: Berkeley
Low Density Parity Check Decoder Architecture Engling Yeo yeo@eecs.berkeley.edu Department of Electrical Engineering and Computer Sciences University of California, Berkeley Engling Yeo University of California, Berkeley 1 Lowdensity Parity Chec

Lec24_06
School: Berkeley

L1magic
School: Berkeley
1 magic : Recovery of Sparse Signals via Convex Programming Emmanuel Cand`s and Justin Romberg, Caltech e October 2005 1 Seven problems A recent series of papers [38] develops a theory of signal recovery from highly incomplete information. The

Lec9
School: Berkeley

EE225C_Proposal_ammer_sheets
School: Berkeley
Timing Recovery Unit for a 1.6 Mbps DSSS Receiver EE225C Project Proposal Submitted by Josie Ammer and Mike Sheets September 21, 2000 System Components: Adaptive Pilot Detect and Course Timing Acquisition (APD&CTA) Mike Sheets (msheets@eecs.berk

OFDM_SVD_dejan
School: Berkeley
OFDM Receiver Design: Singular Value Decomposition for Channel Estimation Dejan Markovi dejan@eecs.berkeley.edu EE225C Midterm Report 7 November 2000 SVD Block Description Tx Encoding & Modulatio n Channel z'1 z'4 U Rx x' V x y y' U Demod

Ffc_tutorial
School: Berkeley
A Tutorial on Using SimulinkTM and XilinxTM System Generator to Build Floatingpoint and Fixedpoint Communication Systems For EE225c, 2003 By Changchun Shi Last Updated: March 10, 2003 Berkeley Wireless Research Center EECS Department, University of

Lec16_ofdm
School: Berkeley
E225C Lecture 16 OFDM Introduction EE225C Multipath can be described in two domains: time and frequency Time domain: Impulse response time time time Impulse response Frequency domain: Frequency response time time time Sinusoidal signal as inpu

Comsoc
School: Berkeley
IEEE SCV Communications Society Lecture CMOS for Ultra Wideband and 60 GHz Communications Bob Brodersen Dept. of EECS Univ. of Calif. Berkeley http:/bwrc.eecs.berkeley.edu Berkeley Wireless Research Center FCC  Unlicensed Spectra UWB ISM 0 UPCS U

Hw5
School: Berkeley
EE 225C VLSI Signal Processing Homework 5 Due on April, 2003 The goal of this problem set will be to implement a single carrier, 20 Mbit/sec QPSK transmitter and receiver that uses a synchronizer to compensate for the channel impairments. A prototype

Lab7
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #7 Image Enhancement Overview: Spring 2003 A problem frequently encou

Lecture21
School: Berkeley

Lecture8
School: Berkeley

Lecture4
School: Berkeley

Info225a
School: Berkeley
EECS 225A Digital Signal Processing Gastpar University of California, Berkeley: Spring 2007 January 16, 2007 Course Information (Preliminary Version) 1 Logistics Michael Gastpar, 265 Cory Hall, gastpar@eecs.berkeley.edu, OH Tue Thu 12:401:30 Tue

Hw2
School: Berkeley
EE 225C VLSI Signal Processing Homework 2 Due on March 5, 2003 1. Architectural tradeoffs (a) Calculate the energy efficiency and area efficiency metrics, MOPS/mW and MOPS/mm2 , for the following four chips that appeared in the 2003 ISSCC. (b) Compar

Lec16_ofdm
School: Berkeley
E225C Lecture 16 OFDM Introduction EE225C Introduction to OFDM l Basic idea Using a large number of parallel narrowband subcarriers instead of a single wideband carrier to transport information l Advantages Very easy and efficient in dealing

Lab7
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #5 Image Enhancement Overview: Spring 2008 A problem frequently encou

Lec25
School: Berkeley
1 (Wireless) Networks are more than communications. Part II Prof. Adam Wolisz TUBerlin/Vsiting Scholar UCB EE 225C Spring 2003 Intro . Who: Adam Wolisz Professor of EE&CS at the Technische Universitt Berlin (TUB) Germany Chair of Telecommunic

Wireless_channels
School: Berkeley
Wireless Channels Ada Poon, Bob Brodersen Berkeley Wireless Research Center University of California, Berkeley EarthIonospheric Waveguide 3 30 kHz, very low frequency (VLF) Large wavelength (>10 km) Wave cant penetrate to the lowest layer of ionos

Lec7_06
School: Berkeley

Lec25_06
School: Berkeley

Lec18_06
School: Berkeley

Lec5_06
School: Berkeley

Solnmidterm1
School: Berkeley
EE 225A Spring 2005 First Midterm Exam: Solutions 1. A function of a complex variable z is analytic in a region if (check one): It is continuous at every point in the region. It is differentiable with respect to z at every point in the region. It

Soln04
School: Berkeley
EECS 225A Spring 2005 Homework 4 solutions 1. As shown below, a random variable X is the input to a cascade of two systems with random variable outputs Y1 and Y2 . You are given the joint PDF p X ,Y1 ,Y2 ( x, y1 , y 2 ) and told that it satisfies pY

Hmwk01
School: Berkeley
EECS 225A Spring 2005 Homework 1 Due: January 27. Solutions will be presented on that date and you will selfgrade your homework. Note: In all homework problems you are encouraged to use the numeric and/or symbolic capabilities of Matlab or similar f

Soln05
School: Berkeley
EECS 225A Spring 2005 Homework 5 solutions 1. In the following, Z (k ) = R(k ) + j I (k ) is a zeromean Gaussian random process (meaning R(k ) and I (k m) are zeromean jointly Gaussian for all k and m ) and widesense stationary with autocorrelat

Soln02
School: Berkeley
EECS 225A Spring 2005 Homework 2 solutions 1. Consider a complex signal {z k ,1 k n} . The goal is to find the best approximation to this signal in terms of a complex exponential with some fixed frequency ; that is, the complex coefficients u and

Matrixinversionlemma
School: Berkeley
EECS 225A Spring 2005 Matrix inversion lemma David G Messerschmitt Version 1.0, May 4, 2005 When both A and (A uv H ) are invertible (where A is a square matrix and u and v are column vectors), the matrix inversion lemma states that (A uv H ) 1 A

Soln01
School: Berkeley
EECS 225A Spring 2005 Homework 1 1. Choose any two of the identities involving finite summations in Table 2.3 of Hayes. a. Verify those identities numerically for 0 N 1000 using Matlab. b. Verify those identities for all N using (and trusting) the

Review
School: Berkeley
EECS 225A Spring 2005 Common themes Complex variables Real functions of a complex variable contains z * , not analytic Stationary points * = 0 z Gradient * = 0 z Linear timeinvariant systems Complex exponentials Impulse response, transfer functio

Soln07
School: Berkeley
EECS 225A Spring 2005 Homework 7 solutions 1. You wish to design a leastsquares inverse filter that realizes (or if necessary approximates) g (k ) hN (k ) = d (k ) , 0 k < M . However, battery power limitations restrict the value of N (number of F

Hayeserratatoproblems
School: Berkeley
1 Problem 2.13: The matrix A should be ERRATA in Problems (First Printing) A = ;0 1 1 0 x(n) = A cos(n! + ) Problem 3.8: De ne the process x(n) as follows and, in part (c), let ! be a random variable that is uniformly distributed over the interval

Lec17
School: Berkeley

Lab8
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #8 Image Restoration Overview: Spring 2007 In this assignment, you wi

Lab7
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #7 Image Enhancement Overview: Spring 2007 A problem frequently encou

Hmwk04
School: Berkeley
EECS 225A Spring 2005 Homework 4 Due: February 17 1. As shown below, a random variable X is the input to a cascade of two systems with random variable outputs Y1 and Y2 . You are given the joint PDF p X ,Y1 ,Y2 ( x, y1 , y 2 ) and told that it satisf

Solnmidterm2
School: Berkeley
EE 225A Spring 2005 Second Midterm Exam: Solutions 1. Which of the following properties apply to an arbitrary N N circulant matrix? (Check all that apply; there may be more than one.) Toeplitz Positive definite Symmetric Hermitian Eigenvalues

Info225a
School: Berkeley
EECS 225A Digital Signal Processing Gastpar University of California, Berkeley: Spring 2006 January 17, 2006 Course Information 1 Logistics Michael Gastpar, 265 Cory Hall, gastpar@eecs.berkeley.edu, OH TBA Tuesdays and Thursdays, 23:30, 299 Cory

Lec28a
School: Berkeley
Pyramid Coding and Subband Coding . Basic Idea: Successive lowpass filtering and subsampling. rip" 10.33 Processor generatingthe i + Ith.level image/'.(11. "2) from the ith.levelimage/'{II.1Iz)in Gaussianpyramidimage representation. . Filtering:

Lec13
School: Berkeley

Lab6
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #6 2DFIR filter design J. S. Lim, TwoDimensional Signal and Image Pro

Lecture26
School: Berkeley

Lec22_06
School: Berkeley

ClassInfo
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Information Sheet Lectures Lecturer Wednesdays and Fridays, 11:00am 12:30pm 203 Mc

Ps6
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Ps4
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Ps3
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

UsingVergil
School: Berkeley
7 Using Vergil Authors: Steve Neuendorffer 7.1 Introduction Vergil is the Graphical User Interface for Ptolemy II. This chapter will guide you though using Vergil to create and manipulate Ptolemy models. Figure 7.1 shows a simple Ptolemy II model in

Lab3
School: Berkeley
Experiments 1.3 Adaptive Filtering 1. Generate random sequence of 1 using the DiscreteRandomSource actor. This represents a random sequence of bits to be transmitted over a channel. Filter this sequence with the following filter (the same filter us

Sdf
School: Berkeley
14 SDF Domain Author: Steve Neuendorffer Contributor: Brian Vogel 14.1 Purpose of the Domain The synchronous dataflow (SDF) domain is useful for modeling simple dataflow systems without complicated flow of control, such as signal processing systems.

PracticeProblems
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Lab5
School: Berkeley
Experiments 1.5 Spectral estimation In the spectrum sublibrary of the signal processing library in Ptolemy II, there are three composite actors that perform three different spectral estimation techniques. These are the (1) Spectrum, (2) SmoothedSpec

VCIP08Plenary
School: Berkeley
UC Berkeley Perspectives in distributed source coding Kannan Ramchandran UC Berkeley Media transmission today Highend video camera Mobile device Challenges Lowpower Backend server video sensor Aerial surveillance vehicles High compression e

Lec11c
School: Berkeley

Lec4
School: Berkeley

CSmeetsML
School: Berkeley
Introduction Classication via Sparse Representation Conclusion Compressed Sensing Meets Machine Learning  Classication of Mixture Subspace Models via Sparse Representation Allen Y. Yang <yang@eecs.berkeley.edu> Mini Lectures in Image Processing

Lab6
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #4 2DFIR filter design J. S. Lim, TwoDimensional Signal and Image Pro

CSmeetsMLII
School: Berkeley
Introduction 1 Minimization 0 / 1 Equivalence Conclusion Compressed Sensing Meets Machine Learning  Classication of Mixture Subspace Models via Sparse Representation Allen Y. Yang <yang@eecs.berkeley.edu> Mini Lectures in Image Processing (Pa

ComputerAccounts
School: Berkeley
EE225B Spring 2007 Computer Accounts The EE225B class involves several programming assignments that may be completed using the EECS instructional computers. The information for acquiring access to these computers, as well as downloading software for

Lec2_06
School: Berkeley

Lec8_06
School: Berkeley

Lab7
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #7 Image Enhancement Overview: Spring 2006 A problem frequently encou

OFDM_Rx_Proposal
School: Berkeley
EE225C Fall 2000 Project Proposal OFDM Receiver Design Yun Chiu, Dejan Markovic, Haiyun Tang, Ning Zhang {chiuyun, dejan, tangh, ningzh}@eecs 1. Introduction The advance of digital integrated circuits has made possible the massive DSP computation

Lab3
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Lab Assignment #3 Tomography Overview: Spring 2006 In this assignment, you explo

Lab2
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Lab Assignment #1 Phaseonly image reconstruction Overview: Spring 2006 In this

Lab6
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225b Digital Image Processing Assignment #6 2DFIR Fan Filters Design Overview: Spring 2006 The filter which a

Ofdm
School: Berkeley
EE225C Fall 2000 Final Report 12/12/2000 OFDM Receiver Design Yun Chiu, Dejan Markovic, Haiyun Tang, Ning Zhang {chiuyun, dejan, tangh, ningzh}@eecs.berkeley.edu Abstract Othogonal Frequency Division Multiplex (OFDM) has gained considerable attent

Lec3_06
School: Berkeley

Image_Restoration_99
School: Berkeley
Lagendijk/Biemond: Basic Methods for Image Restoration and Identification 15 February, 1999 BASIC METHODS FOR IMAGE RESTORATION AND IDENTIFICATION Reginald L. Lagendijk and Jan Biemond Information and Communication Theory Group Faculty of Informati

Projects_2008
School: Berkeley
EE225B Projects Spring 2008 You need to do a term project of your choice to satisfy the requirements of the course. The report is due on Friday May 9th in class together with a copy of your presentation. I need both electronic and hard copies of the

Lec12
School: Berkeley
Outline Images and Projection Models Camera Models Camera Intrinsic Parameters Image Formation and Camera Models Allen Y. Yang Berkeley EE 225b Feb 28th, 2007 Allen Y. Yang Image Formation and Camera Models Outline Images and Projection Mode

Lec24
School: Berkeley
Methods of Bit Assignment (cont.) Huffman <2oding: A practical method to achieve nearoptimum perfonnance Example: Message Codeword Probability .,   hOP, () ~ 100 110 1'10 101 1111 Figure 10.16 Illustration of codeword generation in Huffma

Homework1
School: Berkeley

Lec27_06
School: Berkeley

Lec20
School: Berkeley
 ~ '" 'A > :t . . " .",. 1 . "<n 'O , J . " (l,  I l' " .I cJ "';> \l\ , \ J ', . c It "aJ C 'C) \ /tv ( iyJ: . ., \ ShJ \ +I '> ., ,J c ,. .$ < 4S' N <tt ,. r .3 1 " ,. 3 3 .  . '< ",. 1\4 . 2 3 Q

ClassInfo
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225B Digital Image Processing Information Sheet Lectures: Wednesday and Friday, 9:30 11:00 am 203 McLaughlin Sp

ClassInfo
School: Berkeley
University of California, Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Prof. A. Zakhor EE225B Digital Image Processing Information Sheet Lectures: Spring 2007 Wednesdays and Fridays, 9:30 11:00 am 20

Hw4
School: Berkeley

Lab4
School: Berkeley
Experiments 1.4 ADPCM speech coding Consider the same speech file you used in the last assignment, http:/ptolemy.eecs.berkeley.edu/~eal/eecs20/sounds/voice.wav You can read this URL with the AudioReader actor, found in the audio sublibrary of the s

Ps7
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Ps5
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Ps1
School: Berkeley
UNIVERSITY OF CALIFORNIA AT BERKELEY PROF. EDWARD A. LEE COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 518 CORY HALL BERKELEY, CALIFORNIA 94720 TEL: (510) 6420455 FAX: (510) 6422739 EMAIL: eal@eecs.Berkeley.EDU

Sync_franks
School: Berkeley
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. NO. COM28, 8, AUGUST 1980 1107 Carrier and Bit Synchronization in Data CommunicationA Tutorial Review L. E. FRANKS, FELLOW.IEEE AbsrmcrThis paper examines the problems of carrier phase estimation and sy

Lec4_Bee
School: Berkeley
Jan 14th, 2003 Whats BEE? BEE Berkeley Emulation Engine Complete Design & Prototype Environment for Communication Systems Berkeley Wireless Research Center Chen Chang, Kimmo Kuusilinna, Brian Richards, Kevin Camera, Nathan Chan, Allen Chan, Robert

Supplement
School: Berkeley
EE 225A DIGITAL SIGNAL PROCESSING SUPPLEMENTARY MATERIAL 1 EE 225a Digital Signal Processing Supplementary Material 1. Allpass Sequences A sequence h a ( n ) is said to be allpass if it has a DTFT that satisfies Ha ( e ) = 1 . Note that this is t