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

Size: px
Start display at page:

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

Transcription

1 ECE-486 Test 2, Feb 23, 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. Your solutions for time-domain waveforms should all be expressed as real-valued functions. Name : 1. (10%) A continuous-time signal x c (t) is given by x c (t) = 5 cos(2π(10 3 )t) + 2 cos(2π( )t) The signal is sampled at 10 ksps to give a discrete-time signal x[n] (a) Give the equation of x[n]: (b) List all discrete-time frequencies between 0.5 and +0.5 that are present in x[n]: A different signal y[n] is formed by sampling a continuous-time sinusoidal signal y c (t) (still at 10 ksps). The sampled sequence is given by y[n] = 3 cos(0.4πn) (c) Considering the possibility of aliasing, find all of the possible frequencies of the signal y c (t).

2 2. (25%) A causal discrete-time system is described by y[n] + 2y[n 1] + 3 y[n 2] = 2x[n] + 4x[n 1] 4 (a) Find Y (z) if x[n] = (0.1) n u[n] and y[ 1] = 12, y[ 2] = 8. (No need to evaluate y[n].) (b) Find the system gain H(z), and plot the pole-zero diagram for the system. Shade the appropriate region of convergence on your plot. (c) Find the impulse response of the system. (Please provide a closed-form equation for your result.) (d) Is this a stable system? (justify) (e) Evaluate the DC gain of the system.

3 Work space for Problem 2

4 3. (15%) The system of problem 2 is repeated here: y[n] + 2y[n 1] + 3 y[n 2] = 2x[n] + 4x[n 1] 4 (a) By direct substitution into the difference equation, evaluate the first three samples of the impulse response (n = 0, 1, 2). (Hopefully, your result agrees with problem 2c.) (b) Draw a block diagram of the Direct-Form II implementation of this system. (c) Draw a block diagram of the Direct-Form II Transposed implementation of this system.

5 4. (15%) Find x[n] for the given z-transform. X(z) = 3z z z 3 + z 2 + z z 2 + z < z < 3

6 5. (15%) Design a real, causal second-order IIR filter which meets all of the following constraints. Provide a list of the (real-valued) a 0, a 1, a 2, b 0, b 1, b 2 coefficients for your filter. Causal and Stable. Completely rejects f =.375 cycles/sample. Provides a clear frequency-response peak at f = 0.25 cycles/sample. Has a DC gain of 1.0 (0 db).

7 6. (20%) A time-invariant discrete-time system has transfer function H(z) = (z + 1)(z 1 + 1), z 0 (a) Find the system impulse response. (b) Give a difference equation description of the system. (c) Is this an FIR or an IIR system? (Justify) (d) Is this a stable system? (Justify) (e) Is this a causal system? (Justify) (f) Find and plot H(f) for 0.5 < f < 0.5. (g) Using H(f), find the system output y[n] when the input signal is x[n] = 3 sin(2π(0.1)n).

8 General Definitions X(z) = x[n] = 1 2πj X + (z) = x[n] = 1 2πj Linear Systems y[n] = x[n] h[n] = X(ω) = x[n] = 1 2π k= Y (z) = X(z)H(z) Transform Properties n= x[n]z n X(z)z n 1 dz x[n]z n n=0 X + (z)z n 1 dz, n 0 n= π π Double-Sided Z-Transforms x[n]e jωn X(ω)e jωn dω x[k]h[n k] = k= Y (ω) = X(ω)H(ω) h[k]x[n k] Transform Pairs Double-Sided Z-Transforms δ[n] 1 a n u[n] z z a = 1, z > a 1 az 1 a n u[ n 1] z z a = 1, z < a 1 az 1 na n u[n] na n u[ n 1] a n cos(ω 0 n) u[n] a n sin(ω 0 n) u[n] DTFT ( in the limit ) u[n] e jω0n az (z a) 2 = az 1 (1 az 1, z > a ) 2 az (z a) 2 = az 1 (1 az 1, z < a ) 2 1 az 1 cos(ω 0 ) 1 2az 1 cos(ω 0 ) + a 2, z > a z 2 az 1 sin(ω 0 ) 1 2az 1 cos(ω 0 ) + a 2, z > a z 2 ejω e jω 1 + k= k= πδ(ω 2πk) 2πδ(ω ω 0 2πk) a 1 x 1 [n] + a 2 x 2 [n] a 1 X 1 (z) + a 2 X 2 (z) x[n k] z k X(z) a n x[n] X(z/a) x[n] h[n] X(z)H(z) Single-Sided Z-Transforms Power Series n=0 n=0 x n = 1 1 x x < 1 x n n! = ex x < x[n k] z k X + (z)+x[ k]+x[ k+1]z 1 + +x[ 1]z k+1 x[n + k] z k X + (z) x[k 1]z x[k 2]z 2 x[0]z k DTFT x 1 [n]x 2 [n] 1 2π e jω0n x[n] X(ω ω 0 ) π π X 1 (λ)x 2 (ω λ)dλ General (Standard Trig Identities will be furnished on request) θ 0 π/6 π/4 π/3 π/2 sin(θ) 0 1/2 1/ 2 3/2 1 cos(θ) 1 3/2 1/ 2 1/2 0 tan(θ) 0 1/ ax 2 + bx + c = 0 = x = b ± b 2 4ac 2a

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

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

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

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

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

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

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

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

Discrete Time Fourier Transform

Discrete Time Fourier Transform Discrete Time Fourier Transform Recall that we wrote the sampled signal x s (t) = x(kt)δ(t kt). We calculate its Fourier Transform. We do the following: Ex. Find the Continuous Time Fourier Transform of

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

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

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

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

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

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

Digital Control & Digital Filters. Lectures 1 & 2

Digital Control & Digital Filters. Lectures 1 & 2 Digital Controls & Digital Filters Lectures 1 & 2, Professor Department of Electrical and Computer Engineering Colorado State University Spring 2017 Digital versus Analog Control Systems Block diagrams

More information

ECE 301. Division 2, Fall 2006 Instructor: Mimi Boutin Midterm Examination 3

ECE 301. Division 2, Fall 2006 Instructor: Mimi Boutin Midterm Examination 3 ECE 30 Division 2, Fall 2006 Instructor: Mimi Boutin Midterm Examination 3 Instructions:. Wait for the BEGIN signal before opening this booklet. In the meantime, read the instructions below and fill out

More information

ECE503: Digital Signal Processing Lecture 4

ECE503: Digital Signal Processing Lecture 4 ECE503: Digital Signal Processing Lecture 4 D. Richard Brown III WPI 06-February-2012 WPI D. Richard Brown III 06-February-2012 1 / 29 Lecture 4 Topics 1. Motivation for the z-transform. 2. Definition

More information

ECE 301 Division 1, Fall 2006 Instructor: Mimi Boutin Final Examination

ECE 301 Division 1, Fall 2006 Instructor: Mimi Boutin Final Examination ECE 30 Division, all 2006 Instructor: Mimi Boutin inal Examination Instructions:. Wait for the BEGIN signal before opening this booklet. In the meantime, read the instructions below and fill out the requested

More information

Like bilateral Laplace transforms, ROC must be used to determine a unique inverse z-transform.

Like bilateral Laplace transforms, ROC must be used to determine a unique inverse z-transform. Inversion of the z-transform Focus on rational z-transform of z 1. Apply partial fraction expansion. Like bilateral Laplace transforms, ROC must be used to determine a unique inverse z-transform. Let X(z)

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

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

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

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

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

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

Z-TRANSFORMS. Solution: Using the definition (5.1.2), we find: for case (b). y(n)= h(n) x(n) Y(z)= H(z)X(z) (convolution) (5.1.

Z-TRANSFORMS. Solution: Using the definition (5.1.2), we find: for case (b). y(n)= h(n) x(n) Y(z)= H(z)X(z) (convolution) (5.1. 84 5. Z-TRANSFORMS 5 z-transforms Solution: Using the definition (5..2), we find: for case (a), and H(z) h 0 + h z + h 2 z 2 + h 3 z 3 2 + 3z + 5z 2 + 2z 3 H(z) h 0 + h z + h 2 z 2 + h 3 z 3 + h 4 z 4

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

Lecture 04: Discrete Frequency Domain Analysis (z-transform)

Lecture 04: Discrete Frequency Domain Analysis (z-transform) Lecture 04: Discrete Frequency Domain Analysis (z-transform) John Chiverton School of Information Technology Mae Fah Luang University 1st Semester 2009/ 2552 Outline Overview Lecture Contents Introduction

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

ESE 531: Digital Signal Processing

ESE 531: Digital Signal Processing ESE 531: Digital Signal Processing Lec 6: January 30, 2018 Inverse z-transform Lecture Outline! z-transform " Tie up loose ends " Regions of convergence properties! Inverse z-transform " Inspection " Partial

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

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

ECE 301 Division 1, Fall 2008 Instructor: Mimi Boutin Final Examination Instructions:

ECE 301 Division 1, Fall 2008 Instructor: Mimi Boutin Final Examination Instructions: ECE 30 Division, all 2008 Instructor: Mimi Boutin inal Examination Instructions:. Wait for the BEGIN signal before opening this booklet. In the meantime, read the instructions below and fill out the requested

More information

Z-Transform. The Z-transform is the Discrete-Time counterpart of the Laplace Transform. Laplace : G(s) = g(t)e st dt. Z : G(z) =

Z-Transform. The Z-transform is the Discrete-Time counterpart of the Laplace Transform. Laplace : G(s) = g(t)e st dt. Z : G(z) = Z-Transform The Z-transform is the Discrete-Time counterpart of the Laplace Transform. Laplace : G(s) = Z : G(z) = It is Used in Digital Signal Processing n= g(t)e st dt g[n]z n Used to Define Frequency

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

VI. Z Transform and DT System Analysis

VI. Z Transform and DT System Analysis Summer 2008 Signals & Systems S.F. Hsieh VI. Z Transform and DT System Analysis Introduction Why Z transform? a DT counterpart of the Laplace transform in CT. Generalization of DT Fourier transform: z

More information

Signals and Systems Lecture 8: Z Transform

Signals and Systems Lecture 8: Z Transform Signals and Systems Lecture 8: Z Transform Farzaneh Abdollahi Department of Electrical Engineering Amirkabir University of Technology Winter 2012 Farzaneh Abdollahi Signal and Systems Lecture 8 1/29 Introduction

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

6.003: Signals and Systems

6.003: Signals and Systems 6.003: Signals and Systems Z Transform September 22, 2011 1 2 Concept Map: Discrete-Time Systems Multiple representations of DT systems. Delay R Block Diagram System Functional X + + Y Y Delay Delay X

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

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

Analog vs. discrete signals

Analog vs. discrete signals Analog vs. discrete signals Continuous-time signals are also known as analog signals because their amplitude is analogous (i.e., proportional) to the physical quantity they represent. Discrete-time signals

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

ESE 531: Digital Signal Processing

ESE 531: Digital Signal Processing ESE 531: Digital Signal Processing Lec 6: January 31, 2017 Inverse z-transform Lecture Outline! z-transform " Tie up loose ends " Regions of convergence properties! Inverse z-transform " Inspection " Partial

More information

Signals & Systems Handout #4

Signals & Systems Handout #4 Signals & Systems Handout #4 H-4. Elementary Discrete-Domain Functions (Sequences): Discrete-domain functions are defined for n Z. H-4.. Sequence Notation: We use the following notation to indicate the

More information

School of Information Technology and Electrical Engineering EXAMINATION. ELEC3004 Signals, Systems & Control

School of Information Technology and Electrical Engineering EXAMINATION. ELEC3004 Signals, Systems & Control This exam paper must not be removed from the venue Venue Seat Number Student Number Family Name First Name School of Information Technology and Electrical Engineering EXAMINATION Semester One Final Examinations,

More information

Multidimensional digital signal processing

Multidimensional 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 information

log dx a u = log a e du

log dx a u = log a e du Formuls from Trigonometry: sin A cos A = cosa ± B) = cos A cos B sin A sin B sin A = sin A cos A tn A = tn A tn A sina ± B) = sin A cos B ± cos A sin B tn A±tn B tna ± B) = tn A tn B cos A = cos A sin

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

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

Digital Signal Processing Lecture 9 - Design of Digital Filters - FIR

Digital Signal Processing Lecture 9 - Design of Digital Filters - FIR Digital Signal Processing - Design of Digital Filters - FIR Electrical Engineering and Computer Science University of Tennessee, Knoxville November 3, 2015 Overview 1 2 3 4 Roadmap Introduction Discrete-time

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

X (z) = n= 1. Ã! X (z) x [n] X (z) = Z fx [n]g x [n] = Z 1 fx (z)g. r n x [n] ª e jnω

X (z) = n= 1. Ã! X (z) x [n] X (z) = Z fx [n]g x [n] = Z 1 fx (z)g. r n x [n] ª e jnω 3 The z-transform ² Two advantages with the z-transform:. The z-transform is a generalization of the Fourier transform for discrete-time signals; which encompasses a broader class of sequences. The z-transform

More information

Solutions. Number of Problems: 10

Solutions. Number of Problems: 10 Final Exam February 2nd, 2013 Signals & Systems (151-0575-01) Prof. R. D Andrea Solutions Exam Duration: 150 minutes Number of Problems: 10 Permitted aids: One double-sided A4 sheet. Questions can be answered

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 224 Signals and Systems I Review 1/10

EE 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 information

Discrete-Time David Johns and Ken Martin University of Toronto

Discrete-Time David Johns and Ken Martin University of Toronto Discrete-Time David Johns and Ken Martin University of Toronto (johns@eecg.toronto.edu) (martin@eecg.toronto.edu) University of Toronto 1 of 40 Overview of Some Signal Spectra x c () t st () x s () t xn

More information

Lecture 14: Windowing

Lecture 14: Windowing Lecture 14: Windowing ECE 401: Signal and Image Analysis University of Illinois 3/29/2017 1 DTFT Review 2 Windowing 3 Practical Windows Outline 1 DTFT Review 2 Windowing 3 Practical Windows DTFT Review

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

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

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

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

QUESTION BANK SIGNALS AND SYSTEMS (4 th SEM ECE)

QUESTION 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 information

Solutions. Number of Problems: 10

Solutions. Number of Problems: 10 Final Exam February 9th, 2 Signals & Systems (5-575-) Prof. R. D Andrea Solutions Exam Duration: 5 minutes Number of Problems: Permitted aids: One double-sided A4 sheet. Questions can be answered in English

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

ECGR4124 Digital Signal Processing Midterm Spring 2010

ECGR4124 Digital Signal Processing Midterm Spring 2010 ECGR4124 Digital Signal Processing Midterm Spring 2010 Name: LAST 4 DIGITS of Student Number: Do NOT begin until told to do so Make sure that you have all pages before starting Open book, 1 sheet front/back

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

Final 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. 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 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

ECE 301. Division 3, Fall 2007 Instructor: Mimi Boutin Midterm Examination 3

ECE 301. Division 3, Fall 2007 Instructor: Mimi Boutin Midterm Examination 3 ECE 30 Division 3, all 2007 Instructor: Mimi Boutin Midterm Examination 3 Instructions:. Wait for the BEGIN signal before opening this booklet. In the meantime, read the instructions below and fill out

More information

School of Information Technology and Electrical Engineering EXAMINATION. ELEC3004 Signals, Systems & Control

School of Information Technology and Electrical Engineering EXAMINATION. ELEC3004 Signals, Systems & Control This exam paper must not be removed from the venue Venue Seat Number Student Number Family Name First Name School of Information Technology and Electrical Engineering EXAMINATION Semester One Final Examinations,

More information

Discrete Time Fourier Transform (DTFT)

Discrete Time Fourier Transform (DTFT) Discrete Time Fourier Transform (DTFT) 1 Discrete Time Fourier Transform (DTFT) The DTFT is the Fourier transform of choice for analyzing infinite-length signals and systems Useful for conceptual, pencil-and-paper

More information

Multimedia Signals and Systems - Audio and Video. Signal, Image, Video Processing Review-Introduction, MP3 and MPEG2

Multimedia Signals and Systems - Audio and Video. Signal, Image, Video Processing Review-Introduction, MP3 and MPEG2 Multimedia Signals and Systems - Audio and Video Signal, Image, Video Processing Review-Introduction, MP3 and MPEG2 Kunio Takaya Electrical and Computer Engineering University of Saskatchewan December

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

! z-transform. " Tie up loose ends. " Regions of convergence properties. ! Inverse z-transform. " Inspection. " Partial fraction

! z-transform.  Tie up loose ends.  Regions of convergence properties. ! Inverse z-transform.  Inspection.  Partial fraction Lecture Outline ESE 53: Digital Signal Processing Lec 6: January 3, 207 Inverse z-transform! z-transform " Tie up loose ends " gions of convergence properties! Inverse z-transform " Inspection " Partial

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

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

Overview of Discrete-Time Fourier Transform Topics Handy Equations Handy Limits Orthogonality Defined orthogonal

Overview of Discrete-Time Fourier Transform Topics Handy Equations Handy Limits Orthogonality Defined orthogonal Overview of Discrete-Time Fourier Transform Topics Handy equations and its Definition Low- and high- discrete-time frequencies Convergence issues DTFT of complex and real sinusoids Relationship to LTI

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

Complex symmetry Signals and Systems Fall 2015

Complex symmetry Signals and Systems Fall 2015 18-90 Signals and Systems Fall 015 Complex symmetry 1. Complex symmetry This section deals with the complex symmetry property. As an example I will use the DTFT for a aperiodic discrete-time signal. The

More information

EE102B Signal Processing and Linear Systems II. Solutions to Problem Set Nine Spring Quarter

EE102B Signal Processing and Linear Systems II. Solutions to Problem Set Nine Spring Quarter EE02B Signal Processing and Linear Systems II Solutions to Problem Set Nine 202-203 Spring Quarter Problem 9. (25 points) (a) 0.5( + 4z + 6z 2 + 4z 3 + z 4 ) + 0.2z 0.4z 2 + 0.8z 3 x[n] 0.5 y[n] -0.2 Z

More information

ECE 8440 Unit 13 Sec0on Effects of Round- Off Noise in Digital Filters

ECE 8440 Unit 13 Sec0on Effects of Round- Off Noise in Digital Filters ECE 8440 Unit 13 Sec0on 6.9 - Effects of Round- Off Noise in Digital Filters 1 We have already seen that if a wide- sense staonary random signal x(n) is applied as input to a LTI system, the power density

More information

z-transform Chapter 6

z-transform Chapter 6 z-transform Chapter 6 Dr. Iyad djafar Outline 2 Definition Relation Between z-transform and DTFT Region of Convergence Common z-transform Pairs The Rational z-transform The Inverse z-transform z-transform

More information

EE 438 Essential Definitions and Relations

EE 438 Essential Definitions and Relations May 2004 EE 438 Essential Definitions and Relations CT Metrics. Energy E x = x(t) 2 dt 2. Power P x = lim T 2T T / 2 T / 2 x(t) 2 dt 3. root mean squared value x rms = P x 4. Area A x = x(t) dt 5. Average

More information

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

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

More information

Lecture 10. Digital Signal Processing. Chapter 7. Discrete Fourier transform DFT. Mikael Swartling Nedelko Grbic Bengt Mandersson. rev.

Lecture 10. Digital Signal Processing. Chapter 7. Discrete Fourier transform DFT. Mikael Swartling Nedelko Grbic Bengt Mandersson. rev. Lecture 10 Digital Signal Processing Chapter 7 Discrete Fourier transform DFT Mikael Swartling Nedelko Grbic Bengt Mandersson rev. 016 Department of Electrical and Information Technology Lund University

More information

x[n] = x a (nt ) x a (t)e jωt dt while the discrete time signal x[n] has the discrete-time Fourier transform x[n]e jωn

x[n] = x a (nt ) x a (t)e jωt dt while the discrete time signal x[n] has the discrete-time Fourier transform x[n]e jωn Sampling Let x a (t) be a continuous time signal. The signal is sampled by taking the signal value at intervals of time T to get The signal x(t) has a Fourier transform x[n] = x a (nt ) X a (Ω) = x a (t)e

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

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

# FIR. [ ] = b k. # [ ]x[ n " k] [ ] = h k. x[ n] = Ae j" e j# ˆ n Complex exponential input. [ ]Ae j" e j ˆ. ˆ )Ae j# e j ˆ. y n. y n.

# FIR. [ ] = b k. # [ ]x[ n  k] [ ] = h k. x[ n] = Ae j e j# ˆ n Complex exponential input. [ ]Ae j e j ˆ. ˆ )Ae j# e j ˆ. y n. y n. [ ] = h k M [ ] = b k x[ n " k] FIR k= M [ ]x[ n " k] convolution k= x[ n] = Ae j" e j ˆ n Complex exponential input [ ] = h k M % k= [ ]Ae j" e j ˆ % M = ' h[ k]e " j ˆ & k= k = H (" ˆ )Ae j e j ˆ ( )

More information

Discrete Fourier Transform

Discrete Fourier Transform Discrete Fourier Transform Virtually all practical signals have finite length (e.g., sensor data, audio records, digital images, stock values, etc). Rather than considering such signals to be zero-padded

More information

Problem Value

Problem 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 information

Solutions. Number of Problems: 10

Solutions. Number of Problems: 10 Final Exam February 4th, 01 Signals & Systems (151-0575-01) Prof. R. D Andrea Solutions Exam Duration: 150 minutes Number of Problems: 10 Permitted aids: One double-sided A4 sheet. Questions can be answered

More information

6.003 Signal Processing

6.003 Signal Processing 6.003 Signal Processing Week 6, Lecture A: The Discrete Fourier Transform (DFT) Adam Hartz hz@mit.edu What is 6.003? What is a signal? Abstractly, a signal is a function that conveys information Signal

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 NOTES DIGITAL SIGNAL PROCESSING III B.TECH II SEMESTER (JNTUK R 13)

LECTURE NOTES DIGITAL SIGNAL PROCESSING III B.TECH II SEMESTER (JNTUK R 13) LECTURE NOTES ON DIGITAL SIGNAL PROCESSING III B.TECH II SEMESTER (JNTUK R 13) FACULTY : B.V.S.RENUKA DEVI (Asst.Prof) / Dr. K. SRINIVASA RAO (Assoc. Prof) DEPARTMENT OF ELECTRONICS AND COMMUNICATIONS

More information

EE 3054: Signals, Systems, and Transforms Spring A causal discrete-time LTI system is described by the equation. y(n) = 1 4.

EE 3054: Signals, Systems, and Transforms Spring A causal discrete-time LTI system is described by the equation. y(n) = 1 4. EE : Signals, Systems, and Transforms Spring 7. A causal discrete-time LTI system is described by the equation Test y(n) = X x(n k) k= No notes, closed book. Show your work. Simplify your answers.. A discrete-time

More information

Frequency-Domain C/S of LTI Systems

Frequency-Domain C/S of LTI Systems Frequency-Domain C/S of LTI Systems x(n) LTI y(n) LTI: Linear Time-Invariant system h(n), the impulse response of an LTI systems describes the time domain c/s. H(ω), the frequency response describes the

More information

6.003 Signal Processing

6.003 Signal Processing 6.003 Signal Processing Week 6, Lecture A: The Discrete Fourier Transform (DFT) Adam Hartz hz@mit.edu What is 6.003? What is a signal? Abstractly, a signal is a function that conveys information Signal

More information