Topics: Discrete transforms; 1 and 2D Filters, sampling, and scanning

Size: px
Start display at page:

Download "Topics: Discrete transforms; 1 and 2D Filters, sampling, and scanning"

Transcription

1 EE 637 Study Solutions - Assignment 3 Topics: Discrete transforms; and D Filters, sampling, and scanning Spring 00 Exam : Problem 3 (sampling Consider a sampling system were the input, s(t = sinc(t, is sampled with period T = / to form the sampled signal x(n = s(nt. After sampling, you determine that you selected the wrong sampling rate, and really need to have sampled the signal at the period T = /4; so you interpolate by a factor of L = to form the signal y(n. a Sketch the signal s(t and its CTFT S(f. What is the Nyquist sampling rate for this signal? S(f = rect ( t b Sketch the signal x(n and also sketch its DTFT X(e jω. ( x(n = s n = δ(n

2 c Sketch x(n after it is up-sampled by L =. d Sketch the interpolation filter s impulse response. h(n = sinc ( L H ( e jω = Lrect ω π L So h(n = sinc, for ω < π

3 e Sketch the signal y(n. y(n = δ(n sinc ( n = sinc f What is the relationship between y(n and s(t? When T = 4 : y(n = s(nt ( ( = sinc n 4 = sinc 3

4 Problem (FIR filters and frequency re- Spring 00 Exam : sponse Consider the linear-space invariant FIR filter given by y(m, n = x(m, n h(m, n where { π if m 5 and n 5 h(m, n = 0 otherwise a Sketch the function h(m, n. You may use any method you prefer to sketch it (i.e. D or 3D sketch, but make sure to clearly show the zero and nonzero values and their locations in the plane. All values in the discrete window will be π. All other values are 0. b Calculate H(e 0, e 0, the DC gain of the FIR filter. H ( e 0, e = h(m, ne jπ(0m+0n = m= 5 n= m= 5 n= 5 = π h(m, n 4

5 c Is this function separable? If so, then give its separable decomposition h(m, n = g(mf(n. Yes, h(m, n = g(mf(n where g(m = { π if m 5 0 otherwise and f(n = { π if n 5 0 otherwise d How many multiplies per output point are required for direct implementation of the FIR filter output? Direct implementation of this filter would require multiplies. e Specify an alternative implementation which uses the separable nature of the FIR filter. Instead of using h(m, n, first filter using g(m, then filter using f(n. f How many multiplies per output point are required for separable implementation of the FIR filter output? This alternate method would only require 0 multiplies per output (five from each filter. 5

6 Spring 007 Exam : Problem (DSFT and D Z-transform Consider the following D system with input x(m, n and output y(m, n. ( y(m, n = x(m, n + λ x(m, n x(m k, n l k= l=. a Is this a linear system? Is this a space invariant system? Yes, it is a linear space invariant system. b What is the D impulse response of this system, h(m, n? h(m, n = δ(m, n( + λ λ δ(m k, n l k= l= ( + 8λ, for m = n = 0 = λ, for m, n, but m 0 and n 0 0, otherwise c Calculate the frequency response, H(e jµ, e jν? H ( e jµ, e jν = ( + λ λ e jµk e jνl k= l= = ( + λ λ e jµk e jνl k= l= = ( + λ λ ( e jµ + + e jµ ( e jν + + e jν = ( + λ λ ( + cos µ ( + cos ν d Describe how the filter behaves when λ is positive and large. For λ > 0 and large, the filter performs sharpening. e Describe how the filter behaves when λ is negative and >. For < λ < 0, the filter performs blurring. 6

7 Spring 007 Exam : Problem (DSFT and D Z-transform Consider the causal linear space invariant system with input x(m, n and output y(m, n that is specified by y(m, n = x(m, n + ay(m, n + by(m, n a Calculate the transfer function H(z, z for this system. H (z, z = az bz b Calculate the value of h(m, n m= n= where h(m, n is the D impulse response of the system. c Calculate the value of H ( e jµ, e jν = ae jµ be jν h(m, n = H ( e j0, e j0 = m n m= n= h(m, n cos(ω o m. a b Let h(m, n = h(m, ncos(ω 0 m H ( e jµ, e jν = ( H e j(µ ω0, e jν + ( H e j(µ+ω0, e jν h(m, n = H ( e j0, e j0 m n = H ( e jω 0, e j0 + H ( e jω 0, e j0 ( ( = ae jw + 0 b ae jw 0 b d Is this system stable for all, none, or some values of (a, b? Justify your answer. The system will be stable for some values of a and b. For instance, it will be unstable for a = b = 0.5 and stable for a = b = 0.. 7

Digital Signal Processing. Midterm 1 Solution

Digital 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 information

Good Luck. EE 637 Final May 4, Spring Name: Instructions: This is a 120 minute exam containing five problems.

Good Luck. EE 637 Final May 4, Spring Name: Instructions: This is a 120 minute exam containing five problems. EE 637 Final May 4, Spring 200 Name: Instructions: This is a 20 minute exam containing five problems. Each problem is worth 20 points for a total score of 00 points You may only use your brain and a pencil

More information

EEL3135: Homework #4

EEL3135: Homework #4 EEL335: Homework #4 Problem : For each of the systems below, determine whether or not the system is () linear, () time-invariant, and (3) causal: (a) (b) (c) xn [ ] cos( 04πn) (d) xn [ ] xn [ ] xn [ 5]

More information

2. Typical Discrete-Time Systems All-Pass Systems (5.5) 2.2. Minimum-Phase Systems (5.6) 2.3. Generalized Linear-Phase Systems (5.

2. Typical Discrete-Time Systems All-Pass Systems (5.5) 2.2. Minimum-Phase Systems (5.6) 2.3. Generalized Linear-Phase Systems (5. . Typical Discrete-Time Systems.1. All-Pass Systems (5.5).. Minimum-Phase Systems (5.6).3. Generalized Linear-Phase Systems (5.7) .1. All-Pass Systems An all-pass system is defined as a system which has

More information

EE 637 Final April 30, Spring Each problem is worth 20 points for a total score of 100 points

EE 637 Final April 30, Spring Each problem is worth 20 points for a total score of 100 points EE 637 Final April 30, Spring 2018 Name: Instructions: This is a 120 minute exam containing five problems. Each problem is worth 20 points for a total score of 100 points You may only use your brain and

More information

ECE-314 Fall 2012 Review Questions for Midterm Examination II

ECE-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 information

2-D Finite Impulse Response (FIR) Filters. h(k,l)x(m k,n l)

2-D Finite Impulse Response (FIR) Filters. h(k,l)x(m k,n l) C. A. Bouman: Digital Image Processing - January 8, 8 -D Finite Impulse Response (FIR) Filters Difference equation N y(m,n) = k= N N l= N h(k,l)x(m k,n l) ForN = - input points; output point Number of

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Systems Prof. ark Fowler Note Set #28 D-T Systems: DT Filters Ideal & Practical /4 Ideal D-T Filters Just as in the CT case we can specify filters. We looked at the ideal filter for the

More information

EE-210. Signals and Systems Homework 7 Solutions

EE-210. Signals and Systems Homework 7 Solutions EE-20. Signals and Systems Homework 7 Solutions Spring 200 Exercise Due Date th May. Problems Q Let H be the causal system described by the difference equation w[n] = 7 w[n ] 2 2 w[n 2] + x[n ] x[n 2]

More information

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science. Fall Solutions for Problem Set 2

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science. Fall Solutions for Problem Set 2 Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Issued: Tuesday, September 5. 6.: Discrete-Time Signal Processing Fall 5 Solutions for Problem Set Problem.

More information

University of Illinois at Urbana-Champaign ECE 310: Digital Signal Processing

University of Illinois at Urbana-Champaign ECE 310: Digital Signal Processing University of Illinois at Urbana-Champaign ECE 0: Digital Signal Processing Chandra Radhakrishnan PROBLEM SET : SOLUTIONS Peter Kairouz Problem. Hz z 7 z +/9, causal ROC z > contains the unit circle BIBO

More information

Your solutions for time-domain waveforms should all be expressed as real-valued functions.

Your solutions for time-domain waveforms should all be expressed as real-valued functions. ECE-486 Test 2, Feb 23, 2017 2 Hours; Closed book; Allowed calculator models: (a) Casio fx-115 models (b) HP33s and HP 35s (c) TI-30X and TI-36X models. Calculators not included in this list are not permitted.

More information

Solution 7 August 2015 ECE301 Signals and Systems: Final Exam. Cover Sheet

Solution 7 August 2015 ECE301 Signals and Systems: Final Exam. Cover Sheet Solution 7 August 2015 ECE301 Signals and Systems: Final Exam Cover Sheet Test Duration: 120 minutes Coverage: Chap. 1, 2, 3, 4, 5, 7 One 8.5" x 11" crib sheet is allowed. Calculators, textbooks, notes

More information

Signals and Systems. Problem Set: The z-transform and DT Fourier Transform

Signals and Systems. Problem Set: The z-transform and DT Fourier Transform Signals and Systems Problem Set: The z-transform and DT Fourier Transform Updated: October 9, 7 Problem Set Problem - Transfer functions in MATLAB A discrete-time, causal LTI system is described by the

More information

ECE 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 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 information

( ) John A. Quinn Lecture. ESE 531: Digital Signal Processing. Lecture Outline. Frequency Response of LTI System. Example: Zero on Real Axis

( ) John A. Quinn Lecture. ESE 531: Digital Signal Processing. Lecture Outline. Frequency Response of LTI System. Example: Zero on Real Axis John A. Quinn Lecture ESE 531: Digital Signal Processing Lec 15: March 21, 2017 Review, Generalized Linear Phase Systems Penn ESE 531 Spring 2017 Khanna Lecture Outline!!! 2 Frequency Response of LTI System

More information

The 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 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 information

Lecture 19 IIR Filters

Lecture 19 IIR Filters Lecture 19 IIR Filters Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/5/10 1 General IIR Difference Equation IIR system: infinite-impulse response system The most general class

More information

ECE 413 Digital Signal Processing Midterm Exam, Spring Instructions:

ECE 413 Digital Signal Processing Midterm Exam, Spring Instructions: University of Waterloo Department of Electrical and Computer Engineering ECE 4 Digital Signal Processing Midterm Exam, Spring 00 June 0th, 00, 5:0-6:50 PM Instructor: Dr. Oleg Michailovich Student s name:

More information

UNIVERSITY OF OSLO. Please make sure that your copy of the problem set is complete before you attempt to answer anything.

UNIVERSITY OF OSLO. Please make sure that your copy of the problem set is complete before you attempt to answer anything. UNIVERSITY OF OSLO Faculty of mathematics and natural sciences Examination in INF3470/4470 Digital signal processing Day of examination: December 9th, 011 Examination hours: 14.30 18.30 This problem set

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

/ (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 information

Chap 2. Discrete-Time Signals and Systems

Chap 2. Discrete-Time Signals and Systems Digital Signal Processing Chap 2. Discrete-Time Signals and Systems Chang-Su Kim Discrete-Time Signals CT Signal DT Signal Representation 0 4 1 1 1 2 3 Functional representation 1, n 1,3 x[ n] 4, n 2 0,

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science Discrete-Time Signal Processing Fall 2005

MASSACHUSETTS 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 information

New 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 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 information

ELEN 4810 Midterm Exam

ELEN 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 information

NAME: 11 December 2013 Digital Signal Processing I Final Exam Fall Cover Sheet

NAME: 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 information

Review of Fundamentals of Digital Signal Processing

Review of Fundamentals of Digital Signal Processing Solution Manual for Theory and Applications of Digital Speech Processing by Lawrence Rabiner and Ronald Schafer Click here to Purchase full Solution Manual at http://solutionmanuals.info Link download

More information

III. Time Domain Analysis of systems

III. Time Domain Analysis of systems 1 III. Time Domain Analysis of systems Here, we adapt properties of continuous time systems to discrete time systems Section 2.2-2.5, pp 17-39 System Notation y(n) = T[ x(n) ] A. Types of Systems Memoryless

More information

Discrete-time Signals and Systems in

Discrete-time Signals and Systems in Discrete-time Signals and Systems in the Frequency Domain Chapter 3, Sections 3.1-39 3.9 Chapter 4, Sections 4.8-4.9 Dr. Iyad Jafar Outline Introduction The Continuous-Time FourierTransform (CTFT) The

More information

New 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 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 information

Final Exam of ECE301, Section 3 (CRN ) 8 10am, Wednesday, December 13, 2017, Hiler Thtr.

Final 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 information

VII. Discrete Fourier Transform (DFT) Chapter-8. A. Modulo Arithmetic. (n) N is n modulo N, n is an integer variable.

VII. Discrete Fourier Transform (DFT) Chapter-8. A. Modulo Arithmetic. (n) N is n modulo N, n is an integer variable. 1 VII. Discrete Fourier Transform (DFT) Chapter-8 A. Modulo Arithmetic (n) N is n modulo N, n is an integer variable. (n) N = n m N 0 n m N N-1, pick m Ex. (k) 4 W N = e -j2π/n 2 Note that W N k = 0 but

More information

! Introduction. ! Discrete Time Signals & Systems. ! Z-Transform. ! Inverse Z-Transform. ! Sampling of Continuous Time Signals

! Introduction. ! Discrete Time Signals & Systems. ! Z-Transform. ! Inverse Z-Transform. ! Sampling of Continuous Time Signals ESE 531: Digital Signal Processing Lec 25: April 24, 2018 Review Course Content! Introduction! Discrete Time Signals & Systems! Discrete Time Fourier Transform! Z-Transform! Inverse Z-Transform! Sampling

More information

Lecture 11 FIR Filters

Lecture 11 FIR Filters Lecture 11 FIR Filters Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/4/12 1 The Unit Impulse Sequence Any sequence can be represented in this way. The equation is true if k ranges

More information

EE 225D LECTURE ON DIGITAL FILTERS. University of California Berkeley

EE 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 information

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 2 Solutions

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 2 Solutions 8-90 Signals and Systems Profs. Byron Yu and Pulkit Grover Fall 08 Midterm Solutions Name: Andrew ID: Problem Score Max 8 5 3 6 4 7 5 8 6 7 6 8 6 9 0 0 Total 00 Midterm Solutions. (8 points) Indicate whether

More information

Stability Condition in Terms of the Pole Locations

Stability Condition in Terms of the Pole Locations Stability Condition in Terms of the Pole Locations A causal LTI digital filter is BIBO stable if and only if its impulse response h[n] is absolutely summable, i.e., 1 = S h [ n] < n= We now develop a stability

More information

NAME: ht () 1 2π. Hj0 ( ) dω Find the value of BW for the system having the following impulse response.

NAME: 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 information

Problem Value

Problem 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 information

Grades will be determined by the correctness of your answers (explanations are not required).

Grades 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 information

Each problem is worth 25 points, and you may solve the problems in any order.

Each 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 information

Final Exam of ECE301, Prof. Wang s section 8 10am Tuesday, May 6, 2014, EE 129.

Final Exam of ECE301, Prof. Wang s section 8 10am Tuesday, May 6, 2014, EE 129. Final Exam of ECE301, Prof. Wang s section 8 10am Tuesday, May 6, 2014, EE 129. 1. Please make sure that it is your name printed on the exam booklet. Enter your student ID number, e-mail address, and signature

More information

ECGR4124 Digital Signal Processing Final Spring 2009

ECGR4124 Digital Signal Processing Final Spring 2009 ECGR4124 Digital Signal Processing Final Spring 2009 Name: LAST 4 NUMBERS of Student Number: Do NOT begin until told to do so Make sure that you have all pages before starting Open book, 2 sheet front/back

More information

EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 20, Cover Sheet

EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 20, Cover Sheet NAME: NAME EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 20, 2017 Cover Sheet Test Duration: 75 minutes. Coverage: Chaps. 5,7 Open Book but Closed Notes. One 8.5 in. x 11 in. crib sheet

More information

Q1 Q2 Q3 Q4 Q5 Total

Q1 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 information

Interchange of Filtering and Downsampling/Upsampling

Interchange of Filtering and Downsampling/Upsampling Interchange of Filtering and Downsampling/Upsampling Downsampling and upsampling are linear systems, but not LTI systems. They cannot be implemented by difference equations, and so we cannot apply z-transform

More information

Review of Discrete-Time System

Review 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 information

Lecture 2 OKAN UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE

Lecture 2 OKAN UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE OKAN UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE EEE 43 DIGITAL SIGNAL PROCESSING (DSP) 2 DIFFERENCE EQUATIONS AND THE Z- TRANSFORM FALL 22 Yrd. Doç. Dr. Didem Kivanc Tureli didemk@ieee.org didem.kivanc@okan.edu.tr

More information

Review of Fundamentals of Digital Signal Processing

Review of Fundamentals of Digital Signal Processing Chapter 2 Review of Fundamentals of Digital Signal Processing 2.1 (a) This system is not linear (the constant term makes it non linear) but is shift-invariant (b) This system is linear but not shift-invariant

More information

Discrete-Time Fourier Transform (DTFT)

Discrete-Time Fourier Transform (DTFT) Discrete-Time Fourier Transform (DTFT) 1 Preliminaries Definition: The Discrete-Time Fourier Transform (DTFT) of a signal x[n] is defined to be X(e jω ) x[n]e jωn. (1) In other words, the DTFT of x[n]

More information

Solutions: Homework Set # 5

Solutions: Homework Set # 5 Signal Processing for Communications EPFL Winter Semester 2007/2008 Prof. Suhas Diggavi Handout # 22, Tuesday, November, 2007 Solutions: Homework Set # 5 Problem (a) Since h [n] = 0, we have (b) We can

More information

EEE4001F EXAM DIGITAL SIGNAL PROCESSING. University of Cape Town Department of Electrical Engineering PART A. June hours.

EEE4001F EXAM DIGITAL SIGNAL PROCESSING. University of Cape Town Department of Electrical Engineering PART A. June hours. EEE400F EXAM DIGITAL SIGNAL PROCESSING PART A Basic digital signal processing theory.. A sequencex[n] has a zero-phase DTFT X(e jω ) given below: X(e jω ) University of Cape Town Department of Electrical

More information

Discrete-time signals and systems

Discrete-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 information

Discrete-Time Signals and Systems. Frequency Domain Analysis of LTI Systems. The Frequency Response Function. The Frequency Response Function

Discrete-Time Signals and Systems. Frequency Domain Analysis of LTI Systems. The Frequency Response Function. The Frequency Response Function Discrete-Time Signals and s Frequency Domain Analysis of LTI s Dr. Deepa Kundur University of Toronto Reference: Sections 5., 5.2-5.5 of John G. Proakis and Dimitris G. Manolakis, Digital Signal Processing:

More information

Question Bank. UNIT 1 Part-A

Question Bank. UNIT 1 Part-A FATIMA MICHAEL COLLEGE OF ENGINEERING & TECHNOLOGY Senkottai Village, Madurai Sivagangai Main Road, Madurai -625 020 An ISO 9001:2008 Certified Institution Question Bank DEPARTMENT OF ELECTRONICS AND COMMUNICATION

More information

Discrete Time Systems

Discrete Time Systems 1 Discrete Time Systems {x[0], x[1], x[2], } H {y[0], y[1], y[2], } Example: y[n] = 2x[n] + 3x[n-1] + 4x[n-2] 2 FIR and IIR Systems FIR: Finite Impulse Response -- non-recursive y[n] = 2x[n] + 3x[n-1]

More information

Transform Analysis of Linear Time-Invariant Systems

Transform Analysis of Linear Time-Invariant Systems Transform Analysis of Linear Time-Invariant Systems Discrete-Time Signal Processing Chia-Ping Chen Department of Computer Science and Engineering National Sun Yat-Sen University Kaohsiung, Taiwan ROC Transform

More information

Discrete Time Systems

Discrete Time Systems Discrete Time Systems Valentina Hubeika, Jan Černocký DCGM FIT BUT Brno, {ihubeika,cernocky}@fit.vutbr.cz 1 LTI systems In this course, we work only with linear and time-invariant systems. We talked about

More information

Discrete-Time Signals and Systems. The z-transform and Its Application. The Direct z-transform. Region of Convergence. Reference: Sections

Discrete-Time Signals and Systems. The z-transform and Its Application. The Direct z-transform. Region of Convergence. Reference: Sections Discrete-Time Signals and Systems The z-transform and Its Application Dr. Deepa Kundur University of Toronto Reference: Sections 3. - 3.4 of John G. Proakis and Dimitris G. Manolakis, Digital Signal Processing:

More information

EE538 Final Exam Fall 2007 Mon, Dec 10, 8-10 am RHPH 127 Dec. 10, Cover Sheet

EE538 Final Exam Fall 2007 Mon, Dec 10, 8-10 am RHPH 127 Dec. 10, Cover Sheet EE538 Final Exam Fall 2007 Mon, Dec 10, 8-10 am RHPH 127 Dec. 10, 2007 Cover Sheet Test Duration: 120 minutes. Open Book but Closed Notes. Calculators allowed!! This test contains five problems. Each of

More information

Digital Filters Ying Sun

Digital Filters Ying Sun Digital Filters Ying Sun Digital filters Finite impulse response (FIR filter: h[n] has a finite numbers of terms. Infinite impulse response (IIR filter: h[n] has infinite numbers of terms. Causal filter:

More information

EE 521: Instrumentation and Measurements

EE 521: Instrumentation and Measurements Aly El-Osery Electrical Engineering Department, New Mexico Tech Socorro, New Mexico, USA November 1, 2009 1 / 27 1 The z-transform 2 Linear Time-Invariant System 3 Filter Design IIR Filters FIR Filters

More information

Lecture 7 Discrete Systems

Lecture 7 Discrete Systems Lecture 7 Discrete Systems EE 52: Instrumentation and Measurements Lecture Notes Update on November, 29 Aly El-Osery, Electrical Engineering Dept., New Mexico Tech 7. Contents The z-transform 2 Linear

More information

PROBLEM SET 3. Note: This problem set is a little shorter than usual because we have not covered inverse z-transforms yet.

PROBLEM SET 3. Note: This problem set is a little shorter than usual because we have not covered inverse z-transforms yet. PROBLEM SET 3 Issued: /3/9 Due: 2/6/9 Reading: During the past week we concluded our discussion DTFT properties and began our discussion of z-transforms, covering basic calculation of the z-transform and

More information

Grades will be determined by the correctness of your answers (explanations are not required).

Grades 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 information

Digital Signal Processing I Final Exam Fall 2008 ECE Dec Cover Sheet

Digital 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 information

GATE EE Topic wise Questions SIGNALS & SYSTEMS

GATE EE Topic wise Questions SIGNALS & SYSTEMS www.gatehelp.com GATE EE Topic wise Questions YEAR 010 ONE MARK Question. 1 For the system /( s + 1), the approximate time taken for a step response to reach 98% of the final value is (A) 1 s (B) s (C)

More information

Digital Signal Processing

Digital Signal Processing COMP ENG 4TL4: Digital Signal Processing Notes for Lecture #21 Friday, October 24, 2003 Types of causal FIR (generalized) linear-phase filters: Type I: Symmetric impulse response: with order M an even

More information

Digital Signal Processing Lecture 10 - Discrete Fourier Transform

Digital Signal Processing Lecture 10 - Discrete Fourier Transform Digital Signal Processing - Discrete Fourier Transform Electrical Engineering and Computer Science University of Tennessee, Knoxville November 12, 2015 Overview 1 2 3 4 Review - 1 Introduction Discrete-time

More information

Lecture 8: Signal Reconstruction, DT vs CT Processing. 8.1 Reconstruction of a Band-limited Signal from its Samples

Lecture 8: Signal Reconstruction, DT vs CT Processing. 8.1 Reconstruction of a Band-limited Signal from its Samples EE518 Digital Signal Processing University of Washington Autumn 2001 Dept. of Electrical Engineering Lecture 8: Signal Reconstruction, D vs C Processing Oct 24, 2001 Prof: J. Bilmes

More information

ESE 531: Digital Signal Processing

ESE 531: Digital Signal Processing ESE 531: Digital Signal Processing Lec 22: April 10, 2018 Adaptive Filters Penn ESE 531 Spring 2018 Khanna Lecture Outline! Circular convolution as linear convolution with aliasing! Adaptive Filters Penn

More information

University Question Paper Solution

University Question Paper Solution Unit 1: Introduction University Question Paper Solution 1. Determine whether the following systems are: i) Memoryless, ii) Stable iii) Causal iv) Linear and v) Time-invariant. i) y(n)= nx(n) ii) y(t)=

More information

EEM 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: 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 information

EE482: Digital Signal Processing Applications

EE482: Digital Signal Processing Applications Professor Brendan Morris, SEB 3216, brendan.morris@unlv.edu EE482: Digital Signal Processing Applications Spring 2014 TTh 14:30-15:45 CBC C222 Lecture 02 DSP Fundamentals 14/01/21 http://www.ee.unlv.edu/~b1morris/ee482/

More information

ECSE 512 Digital Signal Processing I Fall 2010 FINAL EXAMINATION

ECSE 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 information

ECGR4124 Digital Signal Processing Exam 2 Spring 2017

ECGR4124 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 information

EC Signals and Systems

EC Signals and Systems UNIT I CLASSIFICATION OF SIGNALS AND SYSTEMS Continuous time signals (CT signals), discrete time signals (DT signals) Step, Ramp, Pulse, Impulse, Exponential 1. Define Unit Impulse Signal [M/J 1], [M/J

More information

EE538 Digital Signal Processing I Session 13 Exam 1 Live: Wed., Sept. 18, Cover Sheet

EE538 Digital Signal Processing I Session 13 Exam 1 Live: Wed., Sept. 18, Cover Sheet EE538 Digital Signal Processing I Session 3 Exam Live: Wed., Sept. 8, 00 Cover Sheet Test Duration: 50 minutes. Coverage: Sessions -0. Open Book but Closed Notes. Calculators not allowed. This test contains

More information

Problem Value

Problem 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 information

Digital Signal Processing, Homework 1, Spring 2013, Prof. C.D. Chung

Digital Signal Processing, Homework 1, Spring 2013, Prof. C.D. Chung Digital Signal Processing, Homework, Spring 203, Prof. C.D. Chung. (0.5%) Page 99, Problem 2.2 (a) The impulse response h [n] of an LTI system is known to be zero, except in the interval N 0 n N. The input

More information

Discrete Time Signals and Systems Time-frequency Analysis. Gloria Menegaz

Discrete Time Signals and Systems Time-frequency Analysis. Gloria Menegaz Discrete Time Signals and Systems Time-frequency Analysis Gloria Menegaz Time-frequency Analysis Fourier transform (1D and 2D) Reference textbook: Discrete time signal processing, A.W. Oppenheim and R.W.

More information

NAME: 13 February 2013 EE301 Signals and Systems Exam 1 Cover Sheet

NAME: 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 information

Discrete-time Fourier transform (DTFT) representation of DT aperiodic signals Section The (DT) Fourier transform (or spectrum) of x[n] is

Discrete-time Fourier transform (DTFT) representation of DT aperiodic signals Section The (DT) Fourier transform (or spectrum) of x[n] is Discrete-time Fourier transform (DTFT) representation of DT aperiodic signals Section 5. 3 The (DT) Fourier transform (or spectrum) of x[n] is X ( e jω) = n= x[n]e jωn x[n] can be reconstructed from its

More information

Digital Signal Processing Lecture 4

Digital Signal Processing Lecture 4 Remote Sensing Laboratory Dept. of Information Engineering and Computer Science University of Trento Via Sommarive, 14, I-38123 Povo, Trento, Italy Digital Signal Processing Lecture 4 Begüm Demir E-mail:

More information

Digital Signal Processing Lecture 3 - Discrete-Time Systems

Digital Signal Processing Lecture 3 - Discrete-Time Systems Digital Signal Processing - Discrete-Time Systems Electrical Engineering and Computer Science University of Tennessee, Knoxville August 25, 2015 Overview 1 2 3 4 5 6 7 8 Introduction Three components of

More information

Z Transform (Part - II)

Z Transform (Part - II) Z Transform (Part - II). The Z Transform of the following real exponential sequence x(nt) = a n, nt 0 = 0, nt < 0, a > 0 (a) ; z > (c) for all z z (b) ; z (d) ; z < a > a az az Soln. The given sequence

More information

Linear Convolution Using FFT

Linear Convolution Using FFT Linear Convolution Using FFT Another useful property is that we can perform circular convolution and see how many points remain the same as those of linear convolution. When P < L and an L-point circular

More information

ECE503: Digital Signal Processing Lecture 5

ECE503: Digital Signal Processing Lecture 5 ECE53: Digital Signal Processing Lecture 5 D. Richard Brown III WPI 3-February-22 WPI D. Richard Brown III 3-February-22 / 32 Lecture 5 Topics. Magnitude and phase characterization of transfer functions

More information

University of Illinois at Urbana-Champaign ECE 310: Digital Signal Processing

University of Illinois at Urbana-Champaign ECE 310: Digital Signal Processing University of Illinois at Urbana-Champaign ECE 3: Digital Signal Processing Chandra Radhakrishnan PROBLEM SE 5: SOLUIONS Peter Kairouz Problem o derive x a (t (X a (Ω from X d (ω, we first need to get

More information

BME 50500: Image and Signal Processing in Biomedicine. Lecture 2: Discrete Fourier Transform CCNY

BME 50500: Image and Signal Processing in Biomedicine. Lecture 2: Discrete Fourier Transform CCNY 1 Lucas Parra, CCNY BME 50500: Image and Signal Processing in Biomedicine Lecture 2: Discrete Fourier Transform Lucas C. Parra Biomedical Engineering Department CCNY http://bme.ccny.cuny.edu/faculty/parra/teaching/signal-and-image/

More information

Use: Analysis of systems, simple convolution, shorthand for e jw, stability. Motivation easier to write. Or X(z) = Z {x(n)}

Use: Analysis of systems, simple convolution, shorthand for e jw, stability. Motivation easier to write. Or X(z) = Z {x(n)} 1 VI. Z Transform Ch 24 Use: Analysis of systems, simple convolution, shorthand for e jw, stability. A. Definition: X(z) = x(n) z z - transforms Motivation easier to write Or Note if X(z) = Z {x(n)} z

More information

Final Exam of ECE301, Prof. Wang s section 1 3pm Tuesday, December 11, 2012, Lily 1105.

Final Exam of ECE301, Prof. Wang s section 1 3pm Tuesday, December 11, 2012, Lily 1105. Final Exam of ECE301, Prof. Wang s section 1 3pm Tuesday, December 11, 2012, Lily 1105. 1. Please make sure that it is your name printed on the exam booklet. Enter your student ID number, e-mail address,

More information

EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 19, Cover Sheet

EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 19, Cover Sheet EE301 Signals and Systems In-Class Exam Exam 3 Thursday, Apr. 19, 2012 Cover Sheet Test Duration: 75 minutes. Coverage: Chaps. 5,7 Open Book but Closed Notes. One 8.5 in. x 11 in. crib sheet Calculators

More information

Lecture 7 - IIR Filters

Lecture 7 - IIR Filters Lecture 7 - IIR Filters James Barnes (James.Barnes@colostate.edu) Spring 204 Colorado State University Dept of Electrical and Computer Engineering ECE423 / 2 Outline. IIR Filter Representations Difference

More information

UNIVERSITY OF OSLO. Faculty of mathematics and natural sciences. Forslag til fasit, versjon-01: Problem 1 Signals and systems.

UNIVERSITY OF OSLO. Faculty of mathematics and natural sciences. Forslag til fasit, versjon-01: Problem 1 Signals and systems. UNIVERSITY OF OSLO Faculty of mathematics and natural sciences Examination in INF3470/4470 Digital signal processing Day of examination: December 1th, 016 Examination hours: 14:30 18.30 This problem set

More information

Digital Signal Processing. Midterm 2 Solutions

Digital Signal Processing. Midterm 2 Solutions EE 123 University of California, Berkeley Anant Sahai arch 15, 2007 Digital Signal Processing Instructions idterm 2 Solutions Total time allowed for the exam is 80 minutes Please write your name and SID

More information

EE538 Final Exam Fall :20 pm -5:20 pm PHYS 223 Dec. 17, Cover Sheet

EE538 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 information

Very useful for designing and analyzing signal processing systems

Very useful for designing and analyzing signal processing systems z-transform z-transform The z-transform generalizes the Discrete-Time Fourier Transform (DTFT) for analyzing infinite-length signals and systems Very useful for designing and analyzing signal processing

More information

Chap 4. Sampling of Continuous-Time Signals

Chap 4. Sampling of Continuous-Time Signals Digital Signal Processing Chap 4. Sampling of Continuous-Time Signals Chang-Su Kim Digital Processing of Continuous-Time Signals Digital processing of a CT signal involves three basic steps 1. Conversion

More information

EE 210. Signals and Systems Solutions of homework 2

EE 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 information