ELEG 4603/5173L Digital Signal Processing Ch. 1 Discrete-Time Signals and Systems

Similar documents
ECE 308 Discrete-Time Signals and Systems

Signals and Systems. Problem Set: From Continuous-Time to Discrete-Time

Discrete-Time Signals and Systems. Discrete-Time Signals and Systems. Signal Symmetry. Elementary Discrete-Time Signals.

Review of Discrete-time Signals. ELEC 635 Prof. Siripong Potisuk

Signal Processing. Lecture 02: Discrete Time Signals and Systems. Ahmet Taha Koru, Ph. D. Yildiz Technical University.

Mathematical Description of Discrete-Time Signals. 9/10/16 M. J. Roberts - All Rights Reserved 1

ECE4270 Fundamentals of DSP. Lecture 2 Discrete-Time Signals and Systems & Difference Equations. Overview of Lecture 2. More Discrete-Time Systems

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course

Chapter 2 Systems and Signals

Analog and Digital Signals. Introduction to Digital Signal Processing. Discrete-time Sinusoids. Analog and Digital Signals

Olli Simula T / Chapter 1 3. Olli Simula T / Chapter 1 5

Computing the output response of LTI Systems.

Signal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform

ADVANCED DIGITAL SIGNAL PROCESSING

ELEG3503 Introduction to Digital Signal Processing

EE123 Digital Signal Processing

EE123 Digital Signal Processing

DIGITAL SIGNAL PROCESSING LECTURE 3

Question1 Multiple choices (circle the most appropriate one):

Time-Domain Representations of LTI Systems

Module 18 Discrete Time Signals and Z-Transforms Objective: Introduction : Description: Discrete Time Signal representation

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science. BACKGROUND EXAM September 30, 2004.

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

Discrete-Time Signals and Systems. Signals and Systems. Digital Signals. Discrete-Time Signals. Operations on Sequences: Basic Operations

Digital Signal Processing, Fall 2006

Finite-length Discrete Transforms. Chapter 5, Sections

Solution of Linear Constant-Coefficient Difference Equations

Frequency Response of FIR Filters

Signals & Systems Chapter3

GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING

FIR Filters. Lecture #7 Chapter 5. BME 310 Biomedical Computing - J.Schesser

Discrete-Time System Properties. Discrete-Time System Properties. Terminology: Implication. Terminology: Equivalence. Reference: Section 2.

Solutions - Homework # 1

Solution of EECS 315 Final Examination F09

6.003: Signal Processing

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Generalizing the DTFT. The z Transform. Complex Exponential Excitation. The Transfer Function. Systems Described by Difference Equations

Lecture 2 Linear and Time Invariant Systems

x[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal.

M2.The Z-Transform and its Properties

Web Appendix O - Derivations of the Properties of the z Transform

2D DSP Basics: 2D Systems

Chapter 7 z-transform

Math 312 Lecture Notes One Dimensional Maps

Classification of DT signals

Chapter 7: The z-transform. Chih-Wei Liu

Solutions. Number of Problems: 4. None. Use only the prepared sheets for your solutions. Additional paper is available from the supervisors.

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

Linear time invariant systems

COMM 602: Digital Signal Processing

Ch3 Discrete Time Fourier Transform

Digital Signal Processing, Fall 2010

Digital signal processing: Lecture 5. z-transformation - I. Produced by Qiangfu Zhao (Since 1995), All rights reserved

Chapter 4 : Laplace Transform

Exponential Moving Average Pieter P

A. Basics of Discrete Fourier Transform

Written exam Digital Signal Processing for BMT (8E070). Tuesday November 1, 2011, 09:00 12:00.

Z - Transform. It offers the techniques for digital filter design and frequency analysis of digital signals.

Lecture 3. Digital Signal Processing. Chapter 3. z-transforms. Mikael Swartling Nedelko Grbic Bengt Mandersson. rev. 2016

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

EECE 301 Signals & Systems

6.003 Homework #3 Solutions

Chapter 8. DFT : The Discrete Fourier Transform

Bioengineering 280A Principles of Biomedical Imaging. Fall Quarter 2004 Lecture 2 Linear Systems. Topics

Introduction to Signals and Systems, Part V: Lecture Summary

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The Z-Transform. Content and Figures are from Discrete-Time Signal Processing, 2e by Oppenheim, Shafer, and Buck, Prentice Hall Inc.

Exam. Notes: A single A4 sheet of paper (double sided; hand-written or computer typed)

Discrete-time signals and systems See Oppenheim and Schafer, Second Edition pages 8 93, or First Edition pages 8 79.

EE422G Homework #13 (12 points)

Chapter 3. z-transform

Describing Function: An Approximate Analysis Method

ELEG 5173L Digital Signal Processing Ch. 2 The Z-Transform

ECE-314 Fall 2012 Review Questions

MAS160: Signals, Systems & Information for Media Technology. Problem Set 5. DUE: November 3, (a) Plot of u[n] (b) Plot of x[n]=(0.

1.3 Convergence Theorems of Fourier Series. k k k k. N N k 1. With this in mind, we state (without proof) the convergence of Fourier series.

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Difference Equation Construction (1) ENGG 1203 Tutorial. Difference Equation Construction (2) Grow, baby, grow (1)

} is said to be a Cauchy sequence provided the following condition is true.

Definition of z-transform.

Dynamic Response of Linear Systems

ECE 301: Signals and Systems Homework Assignment #4

ELEC1200: A System View of Communications: from Signals to Packets Lecture 3

FIR Filter Design: Part II

Unit 6: Sequences and Series

Answer: 1(A); 2(C); 3(A); 4(D); 5(B); 6(A); 7(C); 8(C); 9(A); 10(A); 11(A); 12(C); 13(C)

The z-transform can be used to obtain compact transform-domain representations of signals and systems. It

2D DSP Basics: Systems Stability, 2D Sampling

radians A function f ( x ) is called periodic if it is defined for all real x and if there is some positive number P such that:

Unit 4: Polynomial and Rational Functions

EEO 401 Digital Signal Processing Prof. Mark Fowler

6.003 Homework #12 Solutions

EE Midterm Test 1 - Solutions

2.4 - Sequences and Series

DIGITAL FILTER ORDER REDUCTION

AND SYSTEMS 2.0 INTRODUCTION

In number theory we will generally be working with integers, though occasionally fractions and irrationals will come into play.

Spring 2014, EE123 Digital Signal Processing

( a) ( ) 1 ( ) 2 ( ) ( ) 3 3 ( ) =!

6.003 Homework #12 Solutions

Transcription:

Departmet of Electrical Egieerig Uiversity of Arasas ELEG 4603/5173L Digital Sigal Processig Ch. 1 Discrete-Time Sigals ad Systems Dr. Jigxia Wu wuj@uar.edu

OUTLINE 2 Classificatios of discrete-time sigals Elemetary discrete-time sigals Liear time-ivariat LTI discrete-time systems Causality ad stability Differece equatio represetatio of LTI systems

SIGNAL CLASSICIATION 3 Discrete-time sigal A sigal that is defied oly at discrete istats of time. Represeted as x,, 3, 2, 1,0,1,2,3, x cos 4 x 1 2 exp 4

SIGNAL CLASSICIATION 4 Review: Aalog v.s. digital Cotiuous-time sigal xt, cotiuous-time, cotiuous amplitude aalog sigal Example: speech sigal Cotiuous-time, discrete amplitude Example: traffic light 1 0 2 3 0 2 1 Discrete-time sigal x, Discrete-time, discrete-amplitude digital sigal Example: Telegraph, text, roll a dice 1 0 2 3 0 2 1 Discrete-time, cotiuous-amplitude Example: samples of aalog sigal, average mothly temperature

SIGNAL CLASSIFICATION 5 Periodic sigal v.s. aperiodic sigal x x N Periodic sigal The smallest value of N that satisfies this relatio is the fudametal periods. cos Is periodic? cos 2 is periodic if N is a iteger, ad the smallest N is the fudametal period. Example: cos 3 cos 3 cos 4

SIGNAL CLASSIFICATION 6 Sum of two periodic sigals x x 1 2 : fudametal period : fudametal period N 1 N 2 x1 x2 x1 x2 is periodic if both x ad x 1 2 are periodic. Assume N1 p N2 q N pn 2 qn where p ad q are ot divisible of each other. The period is 1

SIGNAL CLASSIFICATION 7 Example: Is the sigal periodic? If it is, what is the fudametal period? 3 1 cos si 9 7 2

SIGNAL CLASSIFICATION 8 Eergy sigal Eergy: E lim N N N x 2 Review: eergy of cotiuous-time sigal x 2 E x t 2 dt Eergy sigal: 0 E

SIGNAL CLASSIFICATION 9 Power sigal Power of discrete-time sigal P lim N 1 2N 1 N N Review: power of cotiuous-time sigal x 2 P lim T 1 2T T T x t 2 dt Power sigal: 0 P

SIGNAL CLASSIFICATION 10 Example Determie if the discrete-time expoetial sigal is a eergy sigal or power sigal x 2 0. 5 0

OUTLINE 11 Classificatios of discrete-time sigals Elemetary discrete-time sigals Liear time-ivariat LTI discrete-time systems Causality ad stability Differece equatio represetatio of LTI systems

ELEMENTARY SIGNALS 12 Basic sigal operatios Time shiftig x shift the sigal to the right by samples Reflectig x x 3 x 3 x Reflectig x with respect to = 0. x x

ELEMENTARY SIGNALS 13 Basic sigal operatios Time scalig Example: Let 1, x 1, x 2 x 2 1 Fid, eve odd

ELEMENTARY SIGNALS 14 Basic sigal operatios Time scalig Example: x [ 1,2,1,0, 2] the always poits to x0 fid x3, x, x 3 3 2 3

ELEMENTARY SIGNALS 15 Uit impulse fuctio 1, 0, 0, 0. time shiftig 1, 0, Uit step fuctio 0, 0, u 1, 0.,. Relatio betwee uit impulse fuctio ad uit step fuctio u u 1 u

ELEMENTARY SIGNALS 16 Expoetial fuctio Complex expoetial fuctio x is periodic if N is a iteger, ad the smallest iteger N is the 0 fudametal period. Example x exp x exp j cos 0 jsi 0 2 0 Are the followig sigals periodic? If periodic, fid fudametal period. 7 x1 exp j 9 x 2 exp j 7 9

OUTLINE 17 Classificatios of discrete-time sigals Elemetary discrete-time sigals Liear time-ivariat LTI discrete-time systems Causality ad stability Differece equatio represetatio of LTI systems

DISCRETE-TIME SYSTEMS 18 Liear system Cosider a system with the followig iput-output relatioship x 1 System y x 2 1 System y 2 The system is liear if it meets the superpositio priciple x1 x2 y1 y2 System Time-ivariat system Cosider a system with the followig iput-output relatioship x y System The system is time-ivariat if a time-shift at the iput leads to the same time-shift at the output x y System

DISCRETE-TIME SYSTEM 19 Impulse respose of a LTI system The respose of the system whe the iput is System h Ay arbitrary discrete-time sigal ca be decomposed as weighted summatio of the uit impulse fuctios Why? E.g. x x x 3 x 3 Recall: x t x t d

DISCRETE-TIME SYSTEM 20 LTI respose to arbitrary iput Ay arbitrary sigal ca be writte as x x Time-ivariat Liear x LTI LTI h x h x LTI y x h

DISCRETE-TIME SYSTEM 21 Covolutio sum x h The covolutio sum of two sigals ad is Respose of LTI system x h x h The output of a LTI system is the covolutio sum of the iput ad the impulse respose of the system. x h x h

DISCRETE-TIME SYSTEM 22 Examples 1. x m 2. x u, h u x h

DISCRETE-TIME SYSTEM 23 Example 3. Fid the step respose of the system with impulse respose 1 2 h 2 cos u 2 3

DISCRETE-TIME SYSTEM 24 Example: x [0,1,2] h [ 1, 2, 3, 4], Let be two sequeces, fid x h

DISCRETE-TIME SYSTEM 25 Properties: commutativity x h h x x h x h h x h x

DISCRETE-TIME SYSTEM 26 Properties: associativity x h h x h h x h h2 1 2 1 2 1 x h y h y 1 1 2 x h h h2 1 y

DISCRETE-TIME SYSTEM 27 Distributivity h h x h x h x 2 1 1 1 x h 1 + y x h1 h2 y h 2

DISCRETE-TIME SYSTSEMS 28 Example Cosider a system show i the figure. Fid the overall impulse respose. h 2 1 h 1 u h 2 u 1 2 3

OUTLINE 29 Classificatios of discrete-time sigals Elemetary discrete-time sigals Liear time-ivariat LTI discrete-time systems Causality ad stability Differece equatio represetatio of LTI systems

CAUSALITY AND STABILITY 30 Causal system A discrete-time system is causal if the output y 0 depeds oly o values of iput for 0 The output does ot deped o future iput. Example: determie whether the followig systems are causal. 2 y x 3x 2 y x 1 1 y x 1 x x 1 3 y x y 1 x

Causality of LTI system A LTI system is causal if ad oly if h=0 for < 0 Why? A sigal x is causal if x=0 for < 0. Example: For LTI systems with impulse resposes give as follows. Fid if the systems are casual. 31 CAUSALITY AND STABILITY 1 h x h x h x y cos2 h cos2 u h 1 u b u a h 1 u b u a h

CAUSALITY AND STABILITY 32 Bouded-iput bouded-output BIBO stable a system is BIBO stable if, for ay bouded iput x, the respose y is also bouded. BIBO stability of LTI system A LTI discrete-time system is BIBO stable if Why? h

CAUSALITY AND STABILITY 33 Example For a LTI system with impulse resposes as follows. Are they BIBO stable? h 0.5 u h 0.5 u h 0.5 h 2 u h 2 u

OUTLINE 34 Classificatios of discrete-time sigals Elemetary discrete-time sigals Liear time-ivariat LTI discrete-time systems Causality ad stability Differece equatio represetatio of LTI systems

DIFFERENCE EQUATION Differece equatio represetatio of LTI discrete-time system Ay LTI discrete-time system ca be represeted as Review: ay LTI cotiuous-time system ca be represeted as 35 M N x b y a 0 0 M N dt t x d b dt t y d a 0 0

DIFFERENCE EQUATION Simulatio diagram 36 1 1 1 0 1 N x b b x x b N y a y a y N N

DIFFERENCE EQUATION 37 Example Draw the simulatio diagram of the LTI system described by the followig differece equatio 2y 3y 1 0.5x x 1 5x 2

DIFFERENCE EQUATION 38 Example The impulse respose of a LTI system is Fid the differece equatio represetatio Draw the simulatio diagram. h [2,3,0,5]