New Mexico - ECE - 321

The first two answers have been taken from one of your friends who did it very well.

New Mexico - ECE - 321

New Mexico - ECE - 321

New Mexico - ECE - 321

EECE 321: Electronics-I(Spring 2006, University of New Mexico)Homework-VII (Due Date: Thursday April 27th, In class)In the class, we learnt about the fabrication process for a CMOS inverter. In the following process, draw the masks used for various ste

New Mexico - ECE - 321

EECE 321: Electronics-I(Spring 2007, University of New Mexico)Homework-IX (For Practice only)1. The voltage waveforms shown below are applied to the JK master-slave flip-flop that was discussed in the class. With the flip-flop initially reset, show the

McMaster - CHEMISTRY - Chem 1A03

You are writing VERSION 1 of this test. Make sure you have correctly entered your version number (1) in the correct column on your scan sheet (see p. 2 for details).Section #1 These questions are worth two marks each._ 1. In the event that your teaching

Hanyang University - ME - master

Home Work. #9Problems 4-6, minimize u = u12 + L + u52 with four constraints ui +1 u i = 1.T Thus A = I , b = 0, B B = K 4 , d = (1,1,1,1) 28.2-4) (Large penalty) = 1,10,100,1000. How many correct digits of u for those ( I + K 4 )u = (1, 0, 0,1)Sol)<M

Hanyang University - ME - master

Home Work. #61. Part I1) Find the exact solution to (0.1) for this f(x). 2) Divide the interval [0, 1] into two sub-intervals [0, h] and [h, h+H], where h+H = 1. Using the notation and definitions beginning on page 299 in your text, write down formulas

Hanyang University - ME - master

Home Work. #6Problem Set 3.53.5.2) Display the nonzeros in L. Sol)K 33 , I 33 K 2 D 9 9 matrix K 3D = kron( I , K 2 D) + kron( K 2 D, I ) = 27 27 matrix<K2D matix><K3D matix = 27x27>2009-05-13Home Work. #6< K 3D = LU >< Use spy >2009-05-13Home

Hanyang University - ME - master

Home Work. #6Problem Set 3.13.1.11) where is the largest error? Sol) (1) exact solution :1 1 u " = x u ' = x 2 + A u = x 3 + Ax + B 2 61 u (0) = u (1) = 0 A = , B = 0 6 1 1 u = x3 + x 6 6(2) approximation:Fi = f ( x)Vi ( x)dx = f ( x )i ( x)dx ( Vi

Hanyang University - ME - master

Home Work. #5P roblem Set 2.42.4.9) (Recommended) I f a t ree has five nodes in a line(four edges), answer the q uestions i n Worked Example 2.5A Sol)->->->->- 1 1 0 0 0 1 1 0 A= 0 0 1 1 0 0 0 1 0 0 , H t 0 1 1 0 0 0 1 1 0 0 AT = 0 1 1 0 0 0 1 1 0 0

Hanyang University - ME - master

Home Work. #5P roblem Set 2.42.4.9) (Recommended) I f a t ree has five nodes in a line(four edges), answer the q uestions i n Worked Example 2.5A Sol)->->->->- 1 1 0 0 0 1 1 0 A= 0 0 1 1 0 0 0 1 0 0 , ' ) 0 1 1 0 0 0 1 1 0 0 AT = 0 1 1 0 0 0 1 1 0 0

Hanyang University - ME - master

Home Work. #3P roblem Set 1.71.7.6) Verify Sol)1 1 max ( AT A) = (3 + 5) a nd its sqeare root A = (1 + 5) . 2 21 1 1 0 T A= , A = 1 1 0 1 e igen value 1 1 A AT = 1 2 1 A AT = 11 T det( A A ) = (1 )(2 ) 1 = 0 2 1 1 max = (3 + 5) , min = (3 5) 2 2

Hanyang University - ME - master

Home Work. #2Problem Set 1.4 1 2 f ( x ) = ( x ) ( x + ) , does allow a free-free 3 31.4.7) A difference of point loads, solution tou ' = f . Find infinitely many solution with u ' (0) = 0 and u ' (1) = 0 .Sol)1 2 u ' = f ( x) = ( x ) ( x + ) 3 301

Hanyang University - ME - master

Home Work. #1Problem Set 1.11.1.2. Computeu (0) = 0 + A+Be0 =0 A = u (1) = 1 + A+Be1 =0-1 1 B= 1- e 1- ed 2u du V2 V 1x + = 1 (- 2 + + ) * u = 1 with u ( x) = x + (e -1) 2 dx dx h h 1- e (1/ h 2 * K + 1/ h *V ) + 2 1 0 0 1/ h 2 * 1 2 1 0 +1/ h * U= 0

Hanyang University - ME - master

function s=latin_hs(xmean,xsd,nsample,nvar) % s=latin_hs(xmean,xsd,nsample,nvar) % LHS from normal distribution, no correlation % method of Stein % Stein, M. 1987. Large Sample Properties of Simulations Using Latin Hypercube Sampling. % Technometrics 29:1

Hanyang University - ME - master

% Sampling utilities % Contents % % Multivariate distribution, no correlation % latin_hs : latin hypercube sampling (LHS) of multivariate normal % distribution % lhsu : LHS of multivariate uniform distribution % lhs_empir : LHS of multivariate empirical d

Hanyang University - ME - master

% example of sampling with corr matrix that is not positive definite c clear all nsample=100; n nvar=8; % no of random samples to be drawn % no of variables 20 1 0.27 0.18 -0.27 0.33 1.00 0.94 0.46 -0.45 10 2 50 5 2]; 1]; -0.38 -0.21 0.34 -0.36 0.46 0.54

Hanyang University - ME - master

% example of sampling c clear all nsample=100; n nvar=6; % no of random samples to be drawn % no of variables % mean % std. deviation 0 0 0 -0.70 -0.95 1.00];xmean=[10 5 4 3 20 10]; xsd=[0.1 1 0.1 1 1 1]; % correlation matrix corr=[ 1.00 0 0 0 0 0 1.00 0

Hanyang University - ME - master

function s=ransamp(xmean,xsd,corr,nsample) % s=ransamp(xmean,xsd,corr,nsample) % random sampling with correlation % Input: % xmean : mean of data (1,nvar) % xsd : std.dev of data (1,nvar) % corr : correlation matrix of the variables (nvar,nvar) % nsample

Hanyang University - ME - master

function [r,i]=ranking(x) % [r,i]=ranking(x) % Ranking of a vector % input: % x : vector (nrow,1) % output: % r : rank of the vector (nrow,1) % i : index vector from the sort routine % n=length(x); [s,i]=sort(x); r(i,1)=[1:n]';(nrow,1)

Hanyang University - ME - master

function rc=rank_corr(corr,nsample) % rc=rank_corr(corr,nsample) % induce rank correlation % method of Iman & Conover % Iman, R. L., and W. J. Conover. 1982. A Distribution-free Approach to % Inducing Rank Correlation Among Input Variables. % Communicatio

Hanyang University - ME - master

% % [L,D,E,pneg]=mchol1(G) % % Given a symmetric matrix G, find a matrix E of "small" norm and c % L, and D such that G+E is Positive Definite, and % % G+E = L*D*L' % % Also, calculate a direction pneg, such that if G is not PD, then % % pneg'*G*pneg < 0

Hanyang University - ME - master

function z = ltqnorm(p) %LTQNORM Lower tail quantile for standard normal distribution. % % Z = LTQNORM(P) returns the lower tail quantile for the standard normal % distribution function. I.e., it returns the Z satisfying Prcfw_X < Z = P, % where X has a s

Hanyang University - ME - master

function s=lhsu(xmin,xmax,nsample) % s=lhsu(xmin,xmax,nsample) % LHS from uniform distribution % Input: % xmin : min of data (1,nvar) % xmax : max of data (1,nvar) % nsample : no. of samples % Output: % s : random sample (nsample,nvar) % Budiman (2003) nv

Hanyang University - ME - master

function z=lhs_stein(xmean,xsd,corr,nsample,ntry) % z=lhs_stein(xmean,xsd,corr,nsample) % LHS with correlation, normal distribution % method of Stein (1987) % Stein, M. 1987. Large Sample Properties of Simulations Using Latin Hypercube Sampling. % Technom

Hanyang University - ME - master

function z=lhs_iman_n(xmean,xsd,corr,nsample,ntry) % z=lhs_iman_n(xmean,xsd,corr,nsample,ntry) % LHS with correlation, normal distribution % Method of Iman & Conover % using mchol for Cholesky decomposition so that corr. matrix is positive definite % % Im

Hanyang University - ME - master

function z=lhs_iman(xmean,xsd,corr,nsample,ntry) % z=lhs_iman(xmean,xsd,corr,nsample,nloop) % LHS with correlation, normal distribution % method of Iman & Conover % Iman, R. L., and W. J. Conover. 1982. A Distribution-free Approach to Inducing Rank Correl

Hanyang University - ME - master

function s=lhs_empirco(data,nsample) % s=lhs_empirco(data,nsample) % perform lhs on multivariate empirical distribution % with correlation % Input: % data : data matrix (ndata,nvar) % nsample : no. of samples % Output: % s : random sample (nsample,nvar) %

Hanyang University - ME - master

function s=lhs_empir(data,nsample) % s=lhs_empir(data,nsample) % perform lhs on multivariate empirical distribution % assume no correlation % Input: % data : data matrix (ndata,nvar) % nsample : no. of samples % Output: % s : random sample (nsample,nvar)

Hanyang University - ME - master

Workshop 6Creating the Solid Model6. Importing Geometry Description Import the following CAD files into ANSYS:Workshop SupplementFebruary 7, 2006 Inventory #002269 W6-2INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1Workshop 6A Importi

Hanyang University - ME - master

Workshop 4ANSYS Basics4. WorkshopANSYS Basics1. 2. 3. Open ANSYS with a jobname of block in the C:\Courses\Intro1 directory Click the RESUME icon to resume block.db Dynamically rotate a model with the 3D driver active: Notice the Model Control Toolba

Hanyang University - ME - master

Workshop 3Getting Started3. WorkshopGetting Started1. 2. 3. Go to START > Programs > ANSYS 10.0 > ANSYS Product LauncherWorkshop SupplementINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1Click on the File Management tab and select the

Hanyang University - ME - master

Workshop 2Introductory Workshop2. Introductory WorkshopOpen ANSYS with the LauncherWorkshop SupplementINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1All of the features shown in this workshop will be explained in detail in later chapte

Hanyang University - ME - master

Workshop SupplementIntroduction to ANSYS Part 1Workshop Supplement Introduction to ANSYS - Part 1Inventory Number: 002269 First Edition ANSYS Release: 10.0 Published Date: February 7, 2006 Registered Trademarks:ANSYS is a registered trademark of SAS I

Hanyang University - ME - master

Chapter 14Short TopicsChapter 14 Short TopicsOverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1In this chapter, we will present some general tips and tricks on how to use ANSYS more ef

Hanyang University - ME - master

Chapter 13PostprocessingChapter 13 - PostprocessingOverview There are many ways to review results in the general postprocessor (POST1), some of which have already been covered.Training ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Par

Hanyang University - ME - master

Chapter 12 Thermal AnalysisOverview Training ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1In this chapter, we will describe the specifics of a thermal analysis. The purpose is two-fold: To reiterate the general analysis procedu

Hanyang University - ME - master

Chapter 11Structural AnalysisChapter 11 Structural AnalysisOverview In this chapter, we will describe the specifics of a structural analysis. The purpose is two-fold: To reiterate the general analysis procedure. To introduce you to structural loads a

Hanyang University - ME - master

Chapter 10SolutionChapter 10 SolutionA. SolversTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1The function of the solver is to solve the system of linear simultaneous equations representing

Hanyang University - ME - master

Chapter 9LoadingChapter 9 - LoadingOverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1The solution step is where we apply loads on the object and let the solver calculate the finite ele

Hanyang University - ME - master

Chapter 8Defining the MaterialChapter 8 Defining the MaterialOverview In this chapter, we discuss units, importing ANSYS defined materials, as well as describe how to define a user defined material.Training ManualFebruary 7, 2006 Inventory #002268 8

Hanyang University - ME - master

Chapter 7Create Finite Element ModelChapter 7 Creating the Finite Element ModelA. OverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1The purpose of this chapter is to discuss the meshin

Hanyang University - ME - master

Chapter 6Creating the Solid ModelChapter 6 Creating the Solid ModelOverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1The purpose of this chapter is to review some preliminary modeling

Hanyang University - ME - master

Chapter 5General Analysis ProcedureChapter 5 - General Analysis ProcedureOverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1The objective of this chapter is outline a general analysis p

Hanyang University - ME - master

Chapter 4ANSYS BasicsChapter 4 - ANSYS BasicsA. OverviewTraining ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1Later in this course you will be using geometrical entities such as volumes, areas, li

Hanyang University - ME - master

Chapter 3Getting StartedChapter 3 Getting StartedA. Interactive vs BatchTwo ways of working with ANSYS: Interactive and Batch Modes Training ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1Interacti

Hanyang University - ME - master

Chapter 2FEA and ANSYSChapter 2 - FEA and ANSYSA. About the CompanyANSYS, Inc. Developer of ANSYS family of products Headquartered in Canonsburg, PA USA (south of Pittsburgh)Training ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part

Hanyang University - ME - master

Chapter 1IntroductionChapter 1 - IntroductionWelcome! Welcome to the Introduction to ANSYS Training Course!Training ManualINTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1 INTRODUCTION TO ANSYS - Part 1This training course covers the ba

Hanyang University - ME - master

Training ManualIntroduction to ANSYS Part 1Training Manual Introduction to ANSYS - Part 1Inventory Number: 002268 First Edition ANSYS Release: 10.0 Published Date: February 7, 2006 Registered Trademarks:ANSYS is a registered trademark of SAS IP Inc. A

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #10 1 0 for 0 | | < 3. for < | | 31. x(t) A/D 3 H(ej ) 2 D/A y (t) H (ej )= Upsampling and downsampling in this order avoids aliasing. PART (a) 2. (b) (c) 400&600 400&600AFTER SAMPLING AFTER FIRST AFTER SECONDFINAL400

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #11. Write the signal as the sum of 3 scaled and delayed pulses:/ V 2 sin(2 2) ej 2 /3 4V 2/ 2 sin(4 4) ej 4 /3 4V 2/ 2 sin(4 4) 4 // / = V sin(2 2) V /2 cos(3 /4) sin(4 4) . / / NOTE: F cfw_real and even=real an

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #2 fghi j YYYNN NNYYY YYNNN YYYNN YYYNY C=causal; S=stable. e Y f N g N h Y k Y N Y Y Y l N Y N N Y m Y N Y Y Y n Y Y Y Y Y#abcde SYNYNY LNYYYN 1. TI Y Y N N Y CYNYNY SYNYYY Key: S=static; L=linear; TI=time-invariant; 2.

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #3z 1 (1z 1 )21a. From handout: Zcfw_u(n) = U (z ) = 11 1 ; Zcfw_nu(n) = z dU = z dz 1 Zcfw_(1 + n)u(n) = (1z1 )2 . ROC: |z | > 1. 1b. From handout: Zcfw_(an + an )u(n) = 1c. Zcfw_(1)n 2n u(n) = Zcfw_( 1 )n u(n) = 2d 1

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #41. y (0) = y (1) + y (2) + x(0) = 0 + 0 + 1 = 1. y (2) = y (1) + y (0) = 1 + 1 = 2. Clearly y (1) = y (0) + y (1) + x(1) = 1 + 0 + 0 = 1. y (3) = y (2) + y (1) = 2 + 1 = 3. works. Take 2-sided Z : H (z ) = z 1 H (z ) +

Michigan - EECS - 451

EECS 451 1a. ck = ck =1 6 3 6SOLUTIONS TO PROBLEM SET #54k 6k 8k 10k 2k 5 1 j 2nk/6 = 6 (3+2ej 6 +1ej 6 +0ej 6 +1ej 6 +2ej 6 ) n=0 x(n)e 4 2 9 4 1 6 cos(k/3) + 6 cos(2k/3). co = 6 ; c1 = c5 = 6 ; c2 = c4 = 0; c3 = 6 .+1b. Time domain: Freq domain:1

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #61. Input x(n) clearly has frequency components only at = 0; = ; and = . 21 Impulse resp. h(n) = 2 ( (n) (n 2) transfer function H (ej ) = 1 (1 e2j ). 2=0: = 2X (ej 0 ) = 5ej 00 ; X (ej 2 ) = 3ej 60 ; X (ej ) = 4ej

Michigan - EECS - 451

EECS 451SOLUTIONS TO PROBLEM SET #71a. Reverse the second sequence: cfw_4, 3, 2, 2 cfw_2, 2, 3, 4, repeat the cycle, and shift: y(0): y(1): y(2): y(3):cfw_1,2,3,1,1,2,3,1 cfw_4,2,2,3,4,2,2,3 cfw_1,2,3,1,1,2,3,1 cfw_3,4,2,2,3,4,2,2 cfw_1,2,3,1,1,2,3,1 c

Michigan - EECS - 451

Michigan - EECS - 451

EECS 451 SOLUTIONS TO PROBLEM SET #9 1a. |H (j )| = 1/| where s = j . H (j 0) = and H (j ) = 0. Y z +1 2 1b. H (z ) = Ha (s = 2 z1 ) = z1 = X(z) y [n] y [n 1] = x[n]+ x[n 1]. z +1 (z )e + e +1 1c. H (ej ) = ej 1 = ej/2 ej/2 ej/2 = j cot(/2) e e 1d. For s

UCSD - PHYS - asaasa

UCSDPhysics2AFall2008Instructor:VivekSharmaQuizTwoINSTRUCTIONS:Enteryournameandcode#inthebottomstripofthefirstpage.Returnthe entiresetofexamsheetswithyourscantron .Usea#2penciltofillyourscantron.Writeyourcode numberandbubbleitinunderEXAMNUMBER.Bubbleinth