Communications and Signal Processing Spring 2017 MSE Exam
|
|
- Norman Powell
- 5 years ago
- Views:
Transcription
1 Communications and Signal Processing Spring 2017 MSE Exam Please obtain your Test ID from the following table. You must write your Test ID and name on each of the pages of this exam. A page with missing Test ID or missing name may be assigned a zero score.
2 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 1 Communications and Signal Processing Spring 2017 MSE Exam Name: Test ID: Please put your Test ID and name on each page of this test. Only write in space provided and do not write on the back of the pages. This test is composed of two parts. You must work four questions from Part 1, and three questions from Part 2. If you answer more than seven questions, we will choose randomly which seven to score. So, please mark below those problems that you wish to have graded. Part I (work 4 problems) Part II (work 3 problems) You may use a calculator, a book of math tables (e.g., CRC tables) and tables of Fourier transform pairs, but no other reference material. The test is three hours long.
3 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 2 1. EEE 203 Signals and Systems Consider a continuous-time linear time-invariant system with impulse response h(t) = δ(t n) where δ(t) is the unit impulse function. n=0 (a) Find and sketch the step response of this system; i.e. the output when the input is u(t), the unit step function. (b) Is this system causal? Justify your answer. (c) Is this system stable? Justify your answer.
4 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 3
5 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 4 2. EEE 350 Random Signal Analysis A 2 1 random vector is given by Answer the following questions: X = [ X1 X 2 ]. (1) (a) Let X 1 = U and X 2 = 3U where var(u) = 1. Find the covariance matrix of the resulting X in in equation (1). You can denote the matrix by any capital letter you chose. (b) For the same X 1 = U and X 2 = 3U as in problem (2a), find the correlation coefficient ρ X 1,X 2. (c) Is the covariance matrix of X computed above in problem (2b) positive definite? Explain why or why not. (d) Now consider arbitrary X 1 and X 2 as in equation (1), i.e., the entries of X are not limited to those given in problem (2a). Under what conditions on X 1 and X 2 is the var(x 1 + X 2 ) =var(x 1 ) without X 2 being a constant? (e) If X 1 and X 2 are jointly Gaussian with the joint PDF [ ] ([ ] [ ]) X N, (2) X find the joint PDF of the transformed [ ] [ random ] [ vector ] W1 1 1 X1 =. (3) 2 3 W 2 X 2
6 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 5
7 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 6 3. EEE 404 Real-Time DSP Consider the following input signal: x(n) = 1, n = 0, 2 1, n = 1, 3 0, otherwise Consider the following impulse response of an LTI system: h(n) = 1, n = 0 1, n = 1 0, otherwise (a) Indicate how the output of the system can be computed using the circular convolution. (b) Compute the output of the system using the circular convolution.
8 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 7
9 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 8 4. EEE 407 Digital Signal Processing Use analog filter approximations to convert a 1st order R-C lowpass filter circuit (RC=1) to a digital filter with: (a) the impulse invariance method. (b) the bilinear transformation. In both cases, give the transfer function of the digital filter.
10 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 9
11 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: EEE 407 Digital Signal Processing Show that the Inverse Discrete Fourier Transform (DFT) can be derived by minimizing e(n) in the least-squares sense, where N 1 e(t) = x(n) c(k)e j2πkn/n n = 0, 1, 2,..., N 1. Define c(k). k=0
12 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 11
13 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: EEE 455 Communication Systems Consider the following signal set: s 1 (t) = A cos(2πf c t) where t [0, T ). s 2 (t) = A sin(2πf c t) (a) What are the basis functions for this signal set? (b) Draw the constellation diagram for this signal set. (c) Find the average energy and minimum distance of this signal set in terms of A.
14 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 13
15 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: EEE 455 Communication Systems Consider the design of an OFDM modulated signal. Assume that the transmitter operates at a 10 MHz complex sample rate, and that the maximum expected delay spread is less than 1 µs. (a) What is the complex sample period, T s (which is not the duration of the OFDM symbol)? (b) To assure orthogonality, what is the minimum number of samples to use for the cyclic prefix? (c) If the OFDM symbol has 100 subcarriers, what is the subcarrier spacing in frequency?
16 Spring 2017 Comm/SP MSE Exam Part I Test ID: Name: 15
17 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 459/591 Communication Networks Consider TCP slow start. Suppose a new TCP connection is just starting up, i.e., sends one maximum size segment (MSS) in the first transmission round. Suppose the Slow Start Threshold is initially 16 MSS. Suppose the connection has an infinite number of MSSs to send. Further, suppose that a triple duplicate ACK occurs at the end of transmission round 8. No other triple-duplicate ACKs or time-outs occur. Tabulate or plot the congestion window (in units of MSS) as a function of time (in units of transmission rounds) for TCP Tahoe and for TCP Reno from transmission round 1 up to and including transmission round 16. Include the Slow Start Threshold in your table or plot.
18 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 17
19 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 505 Time-Frequency Signal Processing The spectrogram time-frequency representation of a signal x(t), with analysis window h(t), is defined as: 2 S x (t, f) = x(τ) h (τ t) e j2πτf dτ. τ (a) Compute and sketch the spectrogram of the sinusoid x(t)=e j600πt using the rectangular window h(t)=u(t) u(t T ), where u(t) is the unit step function and T is the duration of the window. (b) Discuss the time-frequency resolution of the spectrogram in (a) as the window duration T increases.
20 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 19
21 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 506 Digital Spectral Analysis Consider the transmitted communications signal represented by the sequence s m, m Z such that it looks like each element of the sequence was drawn independently from a unit-variance circularly symmetric white complex Gaussian signal. The signal propagates through a dispersive channel, so that the observed signal (where we have ignored any noise) at the receiver z m is given by x m = s m + i s m s m 2. (a) Write down the transfer function H(z) for the channel. (b) Is H(z) stable? Why? (c) Evaluate the power spectral density P (f) in terms of the normalized frequency. You can leave it in terms of exponentials.
22 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 21
23 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 507 Multidimensional Signal Processing Consider the following 2D signal x(n 1, n 2 ) given by: x(n 1, n 2 ) = u(n 1 + 2, n 2 3) δ(n 1 4) Is x(n 1, n 2 ) separable? Justify your answer to receive proper credit.
24 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 23
25 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 508 Digital Image/Video Processing and Compression (a) Rods facilitate sharp vision. (Circle One) Ans: True False (b) Brightness is linearly proportional to luminance. (Circle One) Ans: True False (c) The color of an object depends on the luminance of the surround. (Circle One) Ans: True False (d) There are more cones than rods in the retina. (Circle One) Ans: True False (e) Simple cells have a circular receptive field. (Circle One) Ans: True False
26 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 25
27 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 510 Multimedia Signal Processing A simple two-band Quadrature Mirror Filter (QMF) bank is used for sub-band signal processing. The low band analysis filter is H(z) = 1 + z 1. Assuming no quantization/finite precision noise determine the rest of the filters for alias-free reconstruction.
28 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 27
29 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 552 Digital Communications Find the parameters (b, T ) of the filter h(t) = δ(t) bδ(t T ) to suppress a carrier signal at 900MHz.
30 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 29
31 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 554 Random Signal Theory Consider the random process X(t)=A u(t) + B cos (2πf 0 t), where f 0 is a known frequency and u(t) is the unit step function (which is defined as u(t)=1 for t > 0 and u(t)=0 for t < 0). The two continuous random variables A and B are assumed independent; A is uniformly distributed between -5 and 5, and B has a Gaussian distribution with zero mean and variance 25. (a) Find the mean of the random process X(t). (b) Find the autocorrelation function of the random process X(t). (c) Is the random process X(t) stationary in the wide sense? Justify your answer.
32 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 31
33 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 557 Broadband Networks Let G denote the offered traffic to a slotted Aloha channel and assume that the merged packet arrivals form a Poisson process. That is, P [k transmissions in one slot] = (G) k k! e G. (a) What is the proportion of slots wasted due to collisions? What is the optimal value G to minimize this proportion (i.e., minimize the collisions)? (b) What is the proportion of slots wasted due to either idle slots or collisions? What is the optimal value for G to minimize the wasted slots? (c) What can you conclude from the results you obtain in (1) and (2)? Can you conclude that as long as we minimize the collisions, we can always achieve the maximum throughput?
34 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 33
35 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: EEE 558 Wireless Communications Answer the questions below and be as brief as possible while justifying your answer. For each of the following, please justify your answer by explaining why. (a) Describe a process to estimate the power delay profile. What would the transmitter send, and what would the receiver do to estimate it? (b) Why is the lognormal distribution appropriate to model shadow fading? (c) Name one advantage, and one disadvantage to standardization in wireless. Each should be at most a couple of sentences. (d) Does the Rayleigh fading model fit better for an urban channel model, or a rural channel model? Justify.
36 Spring 2017 Comm/SP MSE Exam Part II Test ID: Name: 35
Electrical Engineering Written PhD Qualifier Exam Spring 2014
Electrical Engineering Written PhD Qualifier Exam Spring 2014 Friday, February 7 th 2014 Please do not write your name on this page or any other page you submit with your work. Instead use the student
More informationNew Mexico State University Klipsch School of Electrical Engineering. EE312 - Signals and Systems I Spring 2018 Exam #1
New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Spring 2018 Exam #1 Name: Prob. 1 Prob. 2 Prob. 3 Prob. 4 Total / 30 points / 20 points / 25 points /
More informationComputer Engineering 4TL4: Digital Signal Processing
Computer Engineering 4TL4: Digital Signal Processing Day Class Instructor: Dr. I. C. BRUCE Duration of Examination: 3 Hours McMaster University Final Examination December, 2003 This examination paper includes
More informationEE538 Final Exam Fall :20 pm -5:20 pm PHYS 223 Dec. 17, Cover Sheet
EE538 Final Exam Fall 005 3:0 pm -5:0 pm PHYS 3 Dec. 17, 005 Cover Sheet Test Duration: 10 minutes. Open Book but Closed Notes. Calculators ARE allowed!! This test contains five problems. Each of the five
More informationECE538 Final Exam Fall 2017 Digital Signal Processing I 14 December Cover Sheet
ECE58 Final Exam Fall 7 Digital Signal Processing I December 7 Cover Sheet Test Duration: hours. Open Book but Closed Notes. Three double-sided 8.5 x crib sheets allowed This test contains five problems.
More informationNAME: ht () 1 2π. Hj0 ( ) dω Find the value of BW for the system having the following impulse response.
University of California at Berkeley Department of Electrical Engineering and Computer Sciences Professor J. M. Kahn, EECS 120, Fall 1998 Final Examination, Wednesday, December 16, 1998, 5-8 pm NAME: 1.
More informationGrades will be determined by the correctness of your answers (explanations are not required).
6.00 (Fall 2011) Final Examination December 19, 2011 Name: Kerberos Username: Please circle your section number: Section Time 2 11 am 1 pm 4 2 pm Grades will be determined by the correctness of your answers
More informationWireless Internet Exercises
Wireless Internet Exercises Prof. Alessandro Redondi 2018-05-28 1 WLAN 1.1 Exercise 1 A Wi-Fi network has the following features: Physical layer transmission rate: 54 Mbps MAC layer header: 28 bytes MAC
More informationGrades will be determined by the correctness of your answers (explanations are not required).
6.00 (Fall 20) Final Examination December 9, 20 Name: Kerberos Username: Please circle your section number: Section Time 2 am pm 4 2 pm Grades will be determined by the correctness of your answers (explanations
More information2016 Spring: The Final Exam of Digital Communications
2016 Spring: The Final Exam of Digital Communications The total number of points is 131. 1. Image of Transmitter Transmitter L 1 θ v 1 As shown in the figure above, a car is receiving a signal from a remote
More informationProblem Value
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 2-May-05 COURSE: ECE-2025 NAME: GT #: LAST, FIRST (ex: gtz123a) Recitation Section: Circle the date & time when
More informationNAME: 23 February 2017 EE301 Signals and Systems Exam 1 Cover Sheet
NAME: 23 February 2017 EE301 Signals and Systems Exam 1 Cover Sheet Test Duration: 75 minutes Coverage: Chaps 1,2 Open Book but Closed Notes One 85 in x 11 in crib sheet Calculators NOT allowed DO NOT
More informationECE 301 Division 1 Exam 1 Solutions, 10/6/2011, 8-9:45pm in ME 1061.
ECE 301 Division 1 Exam 1 Solutions, 10/6/011, 8-9:45pm in ME 1061. Your ID will be checked during the exam. Please bring a No. pencil to fill out the answer sheet. This is a closed-book exam. No calculators
More informationTest 2 Electrical Engineering Bachelor Module 8 Signal Processing and Communications
Test 2 Electrical Engineering Bachelor Module 8 Signal Processing and Communications (201400432) Tuesday May 26, 2015, 14:00-17:00h This test consists of three parts, corresponding to the three courses
More informationELEN 4810 Midterm Exam
ELEN 4810 Midterm Exam Wednesday, October 26, 2016, 10:10-11:25 AM. One sheet of handwritten notes is allowed. No electronics of any kind are allowed. Please record your answers in the exam booklet. Raise
More informationNew Mexico State University Klipsch School of Electrical Engineering. EE312 - Signals and Systems I Fall 2017 Exam #1
New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Fall 2017 Exam #1 Name: Prob. 1 Prob. 2 Prob. 3 Prob. 4 Total / 30 points / 20 points / 25 points / 25
More informationDigital Band-pass Modulation PROF. MICHAEL TSAI 2011/11/10
Digital Band-pass Modulation PROF. MICHAEL TSAI 211/11/1 Band-pass Signal Representation a t g t General form: 2πf c t + φ t g t = a t cos 2πf c t + φ t Envelope Phase Envelope is always non-negative,
More informationECE6604 PERSONAL & MOBILE COMMUNICATIONS. Week 3. Flat Fading Channels Envelope Distribution Autocorrelation of a Random Process
1 ECE6604 PERSONAL & MOBILE COMMUNICATIONS Week 3 Flat Fading Channels Envelope Distribution Autocorrelation of a Random Process 2 Multipath-Fading Mechanism local scatterers mobile subscriber base station
More informationx(t) = t[u(t 1) u(t 2)] + 1[u(t 2) u(t 3)]
ECE30 Summer II, 2006 Exam, Blue Version July 2, 2006 Name: Solution Score: 00/00 You must show all of your work for full credit. Calculators may NOT be used.. (5 points) x(t) = tu(t ) + ( t)u(t 2) u(t
More informationUCSD ECE153 Handout #40 Prof. Young-Han Kim Thursday, May 29, Homework Set #8 Due: Thursday, June 5, 2011
UCSD ECE53 Handout #40 Prof. Young-Han Kim Thursday, May 9, 04 Homework Set #8 Due: Thursday, June 5, 0. Discrete-time Wiener process. Let Z n, n 0 be a discrete time white Gaussian noise (WGN) process,
More informationProbability and Statistics for Final Year Engineering Students
Probability and Statistics for Final Year Engineering Students By Yoni Nazarathy, Last Updated: May 24, 2011. Lecture 6p: Spectral Density, Passing Random Processes through LTI Systems, Filtering Terms
More informationECE-314 Fall 2012 Review Questions for Midterm Examination II
ECE-314 Fall 2012 Review Questions for Midterm Examination II First, make sure you study all the problems and their solutions from homework sets 4-7. Then work on the following additional problems. Problem
More informationName of the Student: Problems on Discrete & Continuous R.Vs
Engineering Mathematics 05 SUBJECT NAME : Probability & Random Process SUBJECT CODE : MA6 MATERIAL NAME : University Questions MATERIAL CODE : JM08AM004 REGULATION : R008 UPDATED ON : Nov-Dec 04 (Scan
More information06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 1
IV. Continuous-Time Signals & LTI Systems [p. 3] Analog signal definition [p. 4] Periodic signal [p. 5] One-sided signal [p. 6] Finite length signal [p. 7] Impulse function [p. 9] Sampling property [p.11]
More informationGEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM. COURSE: ECE 3084A (Prof. Michaels)
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 30-Apr-14 COURSE: ECE 3084A (Prof. Michaels) NAME: STUDENT #: LAST, FIRST Write your name on the front page
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science Discrete-Time Signal Processing Fall 2005
1 MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science 6.341 Discrete-Time Signal Processing Fall 2005 FINAL EXAM Friday, December 16, 2005 Walker (50-340) 1:30pm
More informationECE-340, Spring 2015 Review Questions
ECE-340, Spring 2015 Review Questions 1. Suppose that there are two categories of eggs: large eggs and small eggs, occurring with probabilities 0.7 and 0.3, respectively. For a large egg, the probabilities
More informationThe Johns Hopkins University Department of Electrical and Computer Engineering Introduction to Linear Systems Fall 2002.
The Johns Hopkins University Department of Electrical and Computer Engineering 505.460 Introduction to Linear Systems Fall 2002 Final exam Name: You are allowed to use: 1. Table 3.1 (page 206) & Table
More informationECSE 512 Digital Signal Processing I Fall 2010 FINAL EXAMINATION
FINAL EXAMINATION 9:00 am 12:00 pm, December 20, 2010 Duration: 180 minutes Examiner: Prof. M. Vu Assoc. Examiner: Prof. B. Champagne There are 6 questions for a total of 120 points. This is a closed book
More informationLecture 7: Wireless Channels and Diversity Advanced Digital Communications (EQ2410) 1
Wireless : Wireless Advanced Digital Communications (EQ2410) 1 Thursday, Feb. 11, 2016 10:00-12:00, B24 1 Textbook: U. Madhow, Fundamentals of Digital Communications, 2008 1 / 15 Wireless Lecture 1-6 Equalization
More informationFourier Methods in Digital Signal Processing Final Exam ME 579, Spring 2015 NAME
Fourier Methods in Digital Signal Processing Final Exam ME 579, Instructions for this CLOSED BOOK EXAM 2 hours long. Monday, May 8th, 8-10am in ME1051 Answer FIVE Questions, at LEAST ONE from each section.
More informationQuestion Paper Code : AEC11T02
Hall Ticket No Question Paper Code : AEC11T02 VARDHAMAN COLLEGE OF ENGINEERING (AUTONOMOUS) Affiliated to JNTUH, Hyderabad Four Year B. Tech III Semester Tutorial Question Bank 2013-14 (Regulations: VCE-R11)
More informationProblems on Discrete & Continuous R.Vs
013 SUBJECT NAME SUBJECT CODE MATERIAL NAME MATERIAL CODE : Probability & Random Process : MA 61 : University Questions : SKMA1004 Name of the Student: Branch: Unit I (Random Variables) Problems on Discrete
More informationP 1.5 X 4.5 / X 2 and (iii) The smallest value of n for
DHANALAKSHMI COLLEGE OF ENEINEERING, CHENNAI DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING MA645 PROBABILITY AND RANDOM PROCESS UNIT I : RANDOM VARIABLES PART B (6 MARKS). A random variable X
More informationNAME: 11 December 2013 Digital Signal Processing I Final Exam Fall Cover Sheet
NAME: December Digital Signal Processing I Final Exam Fall Cover Sheet Test Duration: minutes. Open Book but Closed Notes. Three 8.5 x crib sheets allowed Calculators NOT allowed. This test contains four
More informationThe Cooper Union Department of Electrical Engineering ECE111 Signal Processing & Systems Analysis Final May 4, 2012
The Cooper Union Department of Electrical Engineering ECE111 Signal Processing & Systems Analysis Final May 4, 2012 Time: 3 hours. Close book, closed notes. No calculators. Part I: ANSWER ALL PARTS. WRITE
More informationQUESTION BANK SIGNALS AND SYSTEMS (4 th SEM ECE)
QUESTION BANK SIGNALS AND SYSTEMS (4 th SEM ECE) 1. For the signal shown in Fig. 1, find x(2t + 3). i. Fig. 1 2. What is the classification of the systems? 3. What are the Dirichlet s conditions of Fourier
More informationMassachusetts Institute of Technology
Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.011: Introduction to Communication, Control and Signal Processing QUIZ, April 1, 010 QUESTION BOOKLET Your
More informationBasics on 2-D 2 D Random Signal
Basics on -D D Random Signal Spring 06 Instructor: K. J. Ray Liu ECE Department, Univ. of Maryland, College Park Overview Last Time: Fourier Analysis for -D signals Image enhancement via spatial filtering
More informationA Stochastic Model for TCP with Stationary Random Losses
A Stochastic Model for TCP with Stationary Random Losses Eitan Altman, Kostya Avrachenkov Chadi Barakat INRIA Sophia Antipolis - France ACM SIGCOMM August 31, 2000 Stockholm, Sweden Introduction Outline
More informationThis examination consists of 10 pages. Please check that you have a complete copy. Time: 2.5 hrs INSTRUCTIONS
THE UNIVERSITY OF BRITISH COLUMBIA Department of Electrical and Computer Engineering EECE 564 Detection and Estimation of Signals in Noise Final Examination 08 December 2009 This examination consists of
More information6.003 (Fall 2011) Quiz #3 November 16, 2011
6.003 (Fall 2011) Quiz #3 November 16, 2011 Name: Kerberos Username: Please circle your section number: Section Time 2 11 am 3 1 pm 4 2 pm Grades will be determined by the correctness of your answers (explanations
More information3. ESTIMATION OF SIGNALS USING A LEAST SQUARES TECHNIQUE
3. ESTIMATION OF SIGNALS USING A LEAST SQUARES TECHNIQUE 3.0 INTRODUCTION The purpose of this chapter is to introduce estimators shortly. More elaborated courses on System Identification, which are given
More informationEach problem is worth 25 points, and you may solve the problems in any order.
EE 120: Signals & Systems Department of Electrical Engineering and Computer Sciences University of California, Berkeley Midterm Exam #2 April 11, 2016, 2:10-4:00pm Instructions: There are four questions
More informationThis examination consists of 11 pages. Please check that you have a complete copy. Time: 2.5 hrs INSTRUCTIONS
THE UNIVERSITY OF BRITISH COLUMBIA Department of Electrical and Computer Engineering EECE 564 Detection and Estimation of Signals in Noise Final Examination 6 December 2006 This examination consists of
More informationProblem Value Score No/Wrong Rec 3
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING QUIZ #3 DATE: 21-Nov-11 COURSE: ECE-2025 NAME: GT username: LAST, FIRST (ex: gpburdell3) 3 points 3 points 3 points Recitation
More informationFinal Exam of ECE301, Section 3 (CRN ) 8 10am, Wednesday, December 13, 2017, Hiler Thtr.
Final Exam of ECE301, Section 3 (CRN 17101-003) 8 10am, Wednesday, December 13, 2017, Hiler Thtr. 1. Please make sure that it is your name printed on the exam booklet. Enter your student ID number, and
More informationEE 225D LECTURE ON DIGITAL FILTERS. University of California Berkeley
University of California Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences Professors : N.Morgan / B.Gold EE225D Digital Filters Spring,1999 Lecture 7 N.MORGAN
More informationCopyright license. Exchanging Information with the Stars. The goal. Some challenges
Copyright license Exchanging Information with the Stars David G Messerschmitt Department of Electrical Engineering and Computer Sciences University of California at Berkeley messer@eecs.berkeley.edu Talk
More informationNAME: 13 February 2013 EE301 Signals and Systems Exam 1 Cover Sheet
NAME: February EE Signals and Systems Exam Cover Sheet Test Duration: 75 minutes. Coverage: Chaps., Open Book but Closed Notes. One 8.5 in. x in. crib sheet Calculators NOT allowed. This test contains
More informationE2.5 Signals & Linear Systems. Tutorial Sheet 1 Introduction to Signals & Systems (Lectures 1 & 2)
E.5 Signals & Linear Systems Tutorial Sheet 1 Introduction to Signals & Systems (Lectures 1 & ) 1. Sketch each of the following continuous-time signals, specify if the signal is periodic/non-periodic,
More informationEE401: Advanced Communication Theory
EE401: Advanced Communication Theory Professor A. Manikas Chair of Communications and Array Processing Imperial College London Introductory Concepts Prof. A. Manikas (Imperial College) EE.401: Introductory
More informationEE 210. Signals and Systems Solutions of homework 2
EE 2. Signals and Systems Solutions of homework 2 Spring 2 Exercise Due Date Week of 22 nd Feb. Problems Q Compute and sketch the output y[n] of each discrete-time LTI system below with impulse response
More informationTurbulent Flows. U (n) (m s 1 ) on the nth repetition of a turbulent flow experiment. CHAPTER 3: THE RANDOM NATURE OF TURBULENCE
U (n) (m s ) 5 5 2 4 n Figure 3.: Sketch of the value U (n) of the random velocity variable U on the nth repetition of a turbulent flow experiment. (a) x (t) 2-2 (b) (c) x (t) 2-2 4 2 x (t) x (t) -2-4
More informationAspects of Continuous- and Discrete-Time Signals and Systems
Aspects of Continuous- and Discrete-Time Signals and Systems C.S. Ramalingam Department of Electrical Engineering IIT Madras C.S. Ramalingam (EE Dept., IIT Madras) Networks and Systems 1 / 45 Scaling the
More informationCommunication Theory II
Communication Theory II Lecture 8: Stochastic Processes Ahmed Elnakib, PhD Assistant Professor, Mansoura University, Egypt March 5 th, 2015 1 o Stochastic processes What is a stochastic process? Types:
More information2. SPECTRAL ANALYSIS APPLIED TO STOCHASTIC PROCESSES
2. SPECTRAL ANALYSIS APPLIED TO STOCHASTIC PROCESSES 2.0 THEOREM OF WIENER- KHINTCHINE An important technique in the study of deterministic signals consists in using harmonic functions to gain the spectral
More informationPoint-to-Point versus Mobile Wireless Communication Channels
Chapter 1 Point-to-Point versus Mobile Wireless Communication Channels PSfrag replacements 1.1 BANDPASS MODEL FOR POINT-TO-POINT COMMUNICATIONS In this section we provide a brief review of the standard
More informationENT 315 Medical Signal Processing CHAPTER 2 DISCRETE FOURIER TRANSFORM. Dr. Lim Chee Chin
ENT 315 Medical Signal Processing CHAPTER 2 DISCRETE FOURIER TRANSFORM Dr. Lim Chee Chin Outline Introduction Discrete Fourier Series Properties of Discrete Fourier Series Time domain aliasing due to frequency
More informationTherefore the new Fourier coefficients are. Module 2 : Signals in Frequency Domain Problem Set 2. Problem 1
Module 2 : Signals in Frequency Domain Problem Set 2 Problem 1 Let be a periodic signal with fundamental period T and Fourier series coefficients. Derive the Fourier series coefficients of each of the
More informationECE 438 Exam 2 Solutions, 11/08/2006.
NAME: ECE 438 Exam Solutions, /08/006. This is a closed-book exam, but you are allowed one standard (8.5-by-) sheet of notes. No calculators are allowed. Total number of points: 50. This exam counts for
More informationFundamentals of Noise
Fundamentals of Noise V.Vasudevan, Department of Electrical Engineering, Indian Institute of Technology Madras Noise in resistors Random voltage fluctuations across a resistor Mean square value in a frequency
More informationECE 350 Signals and Systems Spring 2011 Final Exam - Solutions. Three 8 ½ x 11 sheets of notes, and a calculator are allowed during the exam.
ECE 35 Spring - Final Exam 9 May ECE 35 Signals and Systems Spring Final Exam - Solutions Three 8 ½ x sheets of notes, and a calculator are allowed during the exam Write all answers neatly and show your
More informationDigital Signal Processing I Final Exam Fall 2008 ECE Dec Cover Sheet
Digital Signal Processing I Final Exam Fall 8 ECE538 7 Dec.. 8 Cover Sheet Test Duration: minutes. Open Book but Closed Notes. Calculators NOT allowed. This test contains FIVE problems. All work should
More informationCommunication Theory Summary of Important Definitions and Results
Signal and system theory Convolution of signals x(t) h(t) = y(t): Fourier Transform: Communication Theory Summary of Important Definitions and Results X(ω) = X(ω) = y(t) = X(ω) = j x(t) e jωt dt, 0 Properties
More information/ (2π) X(e jω ) dω. 4. An 8 point sequence is given by x(n) = {2,2,2,2,1,1,1,1}. Compute 8 point DFT of x(n) by
Code No: RR320402 Set No. 1 III B.Tech II Semester Regular Examinations, Apr/May 2006 DIGITAL SIGNAL PROCESSING ( Common to Electronics & Communication Engineering, Electronics & Instrumentation Engineering,
More informationEEM 409. Random Signals. Problem Set-2: (Power Spectral Density, LTI Systems with Random Inputs) Problem 1: Problem 2:
EEM 409 Random Signals Problem Set-2: (Power Spectral Density, LTI Systems with Random Inputs) Problem 1: Consider a random process of the form = + Problem 2: X(t) = b cos(2π t + ), where b is a constant,
More informationRandom Processes Why we Care
Random Processes Why we Care I Random processes describe signals that change randomly over time. I Compare: deterministic signals can be described by a mathematical expression that describes the signal
More information7 The Waveform Channel
7 The Waveform Channel The waveform transmitted by the digital demodulator will be corrupted by the channel before it reaches the digital demodulator in the receiver. One important part of the channel
More informationMaximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary. Spatial Correlation
Maximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary Spatial Correlation Ahmed K Sadek, Weifeng Su, and K J Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems
More informationEE 16B Final, December 13, Name: SID #:
EE 16B Final, December 13, 2016 Name: SID #: Important Instructions: Show your work. An answer without explanation is not acceptable and does not guarantee any credit. Only the front pages will be scanned
More informationReview of Discrete-Time System
Review of Discrete-Time System Electrical & Computer Engineering University of Maryland, College Park Acknowledgment: ENEE630 slides were based on class notes developed by Profs. K.J. Ray Liu and Min Wu.
More informationEE 224 Signals and Systems I Review 1/10
EE 224 Signals and Systems I Review 1/10 Class Contents Signals and Systems Continuous-Time and Discrete-Time Time-Domain and Frequency Domain (all these dimensions are tightly coupled) SIGNALS SYSTEMS
More informationLab 4: Quantization, Oversampling, and Noise Shaping
Lab 4: Quantization, Oversampling, and Noise Shaping Due Friday 04/21/17 Overview: This assignment should be completed with your assigned lab partner(s). Each group must turn in a report composed using
More informationDigital Signal Processing. Midterm 1 Solution
EE 123 University of California, Berkeley Anant Sahai February 15, 27 Digital Signal Processing Instructions Midterm 1 Solution Total time allowed for the exam is 8 minutes Some useful formulas: Discrete
More informationDiscrete-time signals and systems
Discrete-time signals and systems 1 DISCRETE-TIME DYNAMICAL SYSTEMS x(t) G y(t) Linear system: Output y(n) is a linear function of the inputs sequence: y(n) = k= h(k)x(n k) h(k): impulse response of the
More informationName of the Student: Problems on Discrete & Continuous R.Vs
Engineering Mathematics 08 SUBJECT NAME : Probability & Random Processes SUBJECT CODE : MA645 MATERIAL NAME : University Questions REGULATION : R03 UPDATED ON : November 07 (Upto N/D 07 Q.P) (Scan the
More informationDHANALAKSHMI COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING EC2314- DIGITAL SIGNAL PROCESSING UNIT I INTRODUCTION PART A
DHANALAKSHMI COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING EC2314- DIGITAL SIGNAL PROCESSING UNIT I INTRODUCTION PART A Classification of systems : Continuous and Discrete
More informationECGR4124 Digital Signal Processing Exam 2 Spring 2017
ECGR4124 Digital Signal Processing Exam 2 Spring 2017 Name: LAST 4 NUMBERS of Student Number: Do NOT begin until told to do so Make sure that you have all pages before starting NO TEXTBOOK, NO CALCULATOR,
More informationFinal Exam January 31, Solutions
Final Exam January 31, 014 Signals & Systems (151-0575-01) Prof. R. D Andrea & P. Reist Solutions Exam Duration: Number of Problems: Total Points: Permitted aids: Important: 150 minutes 7 problems 50 points
More informationQ1 Q2 Q3 Q4 Q5 Total
EE 120: Signals & Systems Department of Electrical Engineering and Computer Sciences University of California, Berkeley Midterm Exam #1 February 29, 2016, 2:10-4:00pm Instructions: There are five questions
More informationMultidimensional digital signal processing
PSfrag replacements Two-dimensional discrete signals N 1 A 2-D discrete signal (also N called a sequence or array) is a function 2 defined over thex(n set 1 of, n 2 ordered ) pairs of integers: y(nx 1,
More informationCosc 3451 Signals and Systems. What is a system? Systems Terminology and Properties of Systems
Cosc 3451 Signals and Systems Systems Terminology and Properties of Systems What is a system? an entity that manipulates one or more signals to yield new signals (often to accomplish a function) can be
More informationVALLIAMMAI ENGINEERING COLLEGE. SRM Nagar, Kattankulathur DEPARTMENT OF INFORMATION TECHNOLOGY. Academic Year
VALLIAMMAI ENGINEERING COLLEGE SRM Nagar, Kattankulathur- 603 203 DEPARTMENT OF INFORMATION TECHNOLOGY Academic Year 2016-2017 QUESTION BANK-ODD SEMESTER NAME OF THE SUBJECT SUBJECT CODE SEMESTER YEAR
More information16.584: Random (Stochastic) Processes
1 16.584: Random (Stochastic) Processes X(t): X : RV : Continuous function of the independent variable t (time, space etc.) Random process : Collection of X(t, ζ) : Indexed on another independent variable
More informationPART 1. Review of DSP. f (t)e iωt dt. F(ω) = f (t) = 1 2π. F(ω)e iωt dω. f (t) F (ω) The Fourier Transform. Fourier Transform.
PART 1 Review of DSP Mauricio Sacchi University of Alberta, Edmonton, AB, Canada The Fourier Transform F() = f (t) = 1 2π f (t)e it dt F()e it d Fourier Transform Inverse Transform f (t) F () Part 1 Review
More informationAdaptive Bit-Interleaved Coded OFDM over Time-Varying Channels
Adaptive Bit-Interleaved Coded OFDM over Time-Varying Channels Jin Soo Choi, Chang Kyung Sung, Sung Hyun Moon, and Inkyu Lee School of Electrical Engineering Korea University Seoul, Korea Email:jinsoo@wireless.korea.ac.kr,
More informationEAS 305 Random Processes Viewgraph 1 of 10. Random Processes
EAS 305 Random Processes Viewgraph 1 of 10 Definitions: Random Processes A random process is a family of random variables indexed by a parameter t T, where T is called the index set λ i Experiment outcome
More informationProblem Weight Score Total 100
EE 350 EXAM IV 15 December 2010 Last Name (Print): First Name (Print): ID number (Last 4 digits): Section: DO NOT TURN THIS PAGE UNTIL YOU ARE TOLD TO DO SO Problem Weight Score 1 25 2 25 3 25 4 25 Total
More informationTSKS01 Digital Communication Lecture 1
TSKS01 Digital Communication Lecture 1 Introduction, Repetition, and Noise Modeling Emil Björnson Department of Electrical Engineering (ISY) Division of Communication Systems Emil Björnson Course Director
More informationDigital Signal Processing Module 1 Analysis of Discrete time Linear Time - Invariant Systems
Digital Signal Processing Module 1 Analysis of Discrete time Linear Time - Invariant Systems Objective: 1. To understand the representation of Discrete time signals 2. To analyze the causality and stability
More informationFinal Exam of ECE301, Section 1 (Prof. Chih-Chun Wang) 1 3pm, Friday, December 13, 2016, EE 129.
Final Exam of ECE301, Section 1 (Prof. Chih-Chun Wang) 1 3pm, Friday, December 13, 2016, EE 129. 1. Please make sure that it is your name printed on the exam booklet. Enter your student ID number, and
More information6.02 Fall 2012 Lecture #10
6.02 Fall 2012 Lecture #10 Linear time-invariant (LTI) models Convolution 6.02 Fall 2012 Lecture 10, Slide #1 Modeling Channel Behavior codeword bits in generate x[n] 1001110101 digitized modulate DAC
More informationPower Spectral Density of Digital Modulation Schemes
Digital Communication, Continuation Course Power Spectral Density of Digital Modulation Schemes Mikael Olofsson Emil Björnson Department of Electrical Engineering ISY) Linköping University, SE-581 83 Linköping,
More informationECE302 Spring 2006 Practice Final Exam Solution May 4, Name: Score: /100
ECE302 Spring 2006 Practice Final Exam Solution May 4, 2006 1 Name: Score: /100 You must show ALL of your work for full credit. This exam is open-book. Calculators may NOT be used. 1. As a function of
More informationDigital Signal Processing. Lecture Notes and Exam Questions DRAFT
Digital Signal Processing Lecture Notes and Exam Questions Convolution Sum January 31, 2006 Convolution Sum of Two Finite Sequences Consider convolution of h(n) and g(n) (M>N); y(n) = h(n), n =0... M 1
More informationProblem Value
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 30-Apr-04 COURSE: ECE-2025 NAME: GT #: LAST, FIRST Recitation Section: Circle the date & time when your Recitation
More informationGEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM. COURSE: ECE 3084A (Prof. Michaels)
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 09-Dec-13 COURSE: ECE 3084A (Prof. Michaels) NAME: STUDENT #: LAST, FIRST Write your name on the front page
More informationECE 564/645 - Digital Communications, Spring 2018 Midterm Exam #1 March 22nd, 7:00-9:00pm Marston 220
ECE 564/645 - Digital Communications, Spring 08 Midterm Exam # March nd, 7:00-9:00pm Marston 0 Overview The exam consists of four problems for 0 points (ECE 564) or 5 points (ECE 645). The points for each
More informationOn Coding for Orthogonal Frequency Division Multiplexing Systems
On Coding for Orthogonal Frequency Division Multiplexing Systems Alan Clark Department of Electrical and Computer Engineering A thesis presented for the degree of Doctor of Philosophy University of Canterbury
More information