06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 1
|
|
- Aubrey Webb
- 5 years ago
- Views:
Transcription
1 IV. Continuous-Time Signals & LTI Systems [p. 3] Analog signal definition [p. 4] Periodic signal [p. 5] One-sided signal [p. 6] Finite length signal [p. 7] Impulse function [p. 9] Sampling property [p.11] Impulse properties [p.17] Continuous time system building blocks [p. 18] Delay block [p. 20] Integrator block [p. 25] Differentiator block [p. 26] LTI system [p. 26] Definition [p. 27] Testing for linearity [p. 30] Testing for time invariance [p. 32] Evaluating convolution [p.37] Convolving unit steps [p.38] Convolving impulses [p. 39] Convolution properties [p. 44] Combining LTI systems [p. 47] System stability [p. 51] System causality [p. 53] Examples 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 1
2 Processing of continuous time Signals x ( t ) ANALOG y ( t ) System Analog signal x(t) INFINITE LENGTH SINUSOIDS: (t = time in secs) PERIODIC SIGNALS ONE-SIDED, e.g., for t>0 UNIT STEP: u(t) FINITE LENGTH SQUARE PULSE 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 3
3 CT Signals: PERIODIC Signals of INFINITE DURATION x (t) = 10 cos( 200 π t) Sinusoidal signal Square Wave 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 4
4 CT Signals: ONE-SIDED ut () 1 t 0 = 0 t < 0 Unit step signal One-Sided Sinusoid v(t ) = e t u(t ) Suddenly applied Exponential 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 5
5 CT Signals: FINITE LENGTH p(t) =u(t 2) u(t 4) Square Pulse signal Sinusoid multiplied by a square pulse 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 6
6 What is an Impulse? A signal that is concentrated at one point. δ () t = lim () t δ Δ Δ 0 where δ Δ ( t ) dt = 1 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 7
7 Defining the Impulse δ(t) =0, t 0 One INTUITIVE definition is: Concentrated at t=0 with unit area δ ( τ ) d τ = 1 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 8
8 δ(t) Sampling Property f (t)δ Δ (t) f (0)δ Δ (t) f ( t )δ ( t ) = f (0)δ ( t ) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 9
9 General Sampling Property f (t)δ (t t 0 ) = f (t 0 )δ (t t 0 ) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 10
10 Properties of the Impulse δ (t t 0 ) = 0, t t 0 δ ( t t 0 )dt = 1 f (t)δ(t t 0 ) = f(t 0 )δ(t t 0 ) f ( t ) δ ( t t 0 ) dt = f ( t 0 ) 1 δ ( at) = δ ( t) a du ( t) dt = δ (t) Concentrated at one time Of Unit area Scaling Property Sampling Property Extract one value of f(t) sifting property Derivative of unit step 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 11
11 Example: xt e ut 2( t 1) () = ( 1) Compute and plot dx( t) / dt 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 12
12 Example: Compute: t 1 τ A= δτ ( + 3) e dτ d B= e u t dt C t+ 1 t { 3t ( 1) } = δτ ( + 3) dτ jt D= sin( t) e δ ( τ + 3) dτ 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 13
13 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 14
14 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 15
15 Example: Assume x(t)=u(t)-u(t-5), sketch: 1) dx(t)/dt, 2) x(2-t) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 16
16 CT Building Blocks DELAY by t o INTEGRATOR (CIRCUITS) DIFFERENTIATOR MULTIPLIER & ADDER Others 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 17
17 Ideal Delay: System S x(t) Mathematical Definition: y(t) y(t) = x(t t d ) To find the IMPULSE RESPONSE of a system, h(t), let x(t) be an impulse, so x(t) y(t) System S x(t)=δ(t) y(t)=h(t) ht () =? 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 18
18 Output of Ideal Delay of 1 sec y(t) = x(t 1) = e (t 1) u(t 1) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 19
19 Integrator: x(t) System S y(t) Mathematical Definition: t y ( t ) = x (τ )d τ Running Integral To find the IMPULSE RESPONSE, h(t), let x(t) be an impulse, so t h(t) = δ (τ )dτ = u(t) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 20
20 Integrator: y ( t ) = x (τ ) d τ Integrate the impulse t δ (τ )d τ = u (t ) t IF t<0, we get zero IF t>0, we get one Thus we have h(t) = u(t) for the integrator 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 21
21 Graphical Representation δ (t ) = du (t) dt t 1 t 0 ut () = δτ ( ) dτ= 0 t < 0 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 22
22 Output of Integrator x(t) System S y(t) t y ( t) = x( τ ) dτ y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 23
23 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 24
24 Differentiator: Differentiator Output: Example: x(t) y ( t ) = System S dx (t ) dt y(t) y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 25
25 Linear and Time-Invariant (LTI) Systems If a continuous-time system is both linear and timeinvariant, then the output y(t) is related to the input x(t) by a convolution integral where h(t) is the impulse response of the system. x(t) x(t)=δ(t) System S y(t) h(t)=y(t) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 26
26 Testing for Linearity Identical process to discrete signal case x(t) System S y(t) S x () t + x () t = { α β } 1 2 αs x () t + S x () t Examples: y(t)=2x(t) y(t)=2x(t)+1 y(t)=x(t 2 ) y(t)=x(t-d) { } β { } 1 2 t y () t = x ( τ ) dτ 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 27
27 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 28
28 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 29
29 Testing Time-Invariance A system is time-invariant if a shift in the input produces the same shift in the output x(t) System S y(t) Examples: y(t)=2x(t) y(t)=x(2t) y(t)=x(t-d) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 30
30 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 31
31 Evaluating a Convolution x( t) = u( t 1) t h( t) = e u( t) y( t) = h( τ ) x( t τ ) dτ = h( t) x( t) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 32
32 Solution y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 33
33 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 34
34 Example at bt x() t e = u(), t h() t = e u() t y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 35
35 Special Case: h(t)=u(t) at x() t = e u(), t a 0, h() t = u() t y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 36
36 Convolving Unit Steps x() t = u(), t h() t = u() t y(t)= 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 37
37 Convolution Properties 1) Commutative 2) Associative 3) Distributive 4) Derivative of convolution d dt d x() t y() t = x() t y() t dt d = x() t () dt [ ] [ ] [ y t ] 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 39
38 Convolution Properties 5) Time invariance yt () = xt () ht () xt ( t)* ht ( ) = yt ( t) /12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 40
39 Proofs: 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 41
40 Examples: Compute t A = δ( t 1)*( δ( t+ 2) + 2 e ) d B= sin(5 t) u( t 1/ 2) dt ( ) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 42
41 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 43
42 Cascade of LTI Systems h(t) = h 1 (t) h 2 (t) = h 2 (t) h 1 (t) 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 44
43 Stability A system is stable if every bounded input produces a bounded output. A continuous-time LTI system is stable if and only if h ( t ) dt < 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 47
44 Stability Examples: yt () = 3 xt (), yt () = x( τ ) dτ dx() t yt () =, yt () = txt () dt xt () yt () = e t 0 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 48
45 Note: 1) Finding a counter-example is OK. 2) You can t prove a property with an example 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 49
46 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 50
47 Causal Systems A system is causal if and only if y(t 0 ) depends only on x(τ) for τ< t 0. An LTI system is causal if and only if h( t) = 0 for t < 0 Example: Are the LTI systems with the following imput/output relationships or impulse responses causal? y () t = x( t) 1 y t x t 2 2 () = ( ) h () t = u( t + 3) 2 u( t 3) 3 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 51
48 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 52
49 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 54
50 Example: LTI system h 1 (t)=δ(t+2) LTI system h 2 (t)=δ(t-2) + - LTI system h 3 (t)=u(t Τ) 1) Compute the impulse response to the overall system and plot it 2) How do you need to pick T so that the overall system is causal 3) Are systems 1, 2, 3 causal, is the overall system causal? 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 55
51 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 56
52 Example: 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 57
53 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 58
54 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 59
55 06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 60
Chapter 3 Convolution Representation
Chapter 3 Convolution Representation DT Unit-Impulse Response Consider the DT SISO system: xn [ ] System yn [ ] xn [ ] = δ[ n] If the input signal is and the system has no energy at n = 0, the output yn
More informationTherefore the new Fourier coefficients are. Module 2 : Signals in Frequency Domain Problem Set 2. Problem 1
Module 2 : Signals in Frequency Domain Problem Set 2 Problem 1 Let be a periodic signal with fundamental period T and Fourier series coefficients. Derive the Fourier series coefficients of each of the
More information2. CONVOLUTION. Convolution sum. Response of d.t. LTI systems at a certain input signal
2. CONVOLUTION Convolution sum. Response of d.t. LTI systems at a certain input signal Any signal multiplied by the unit impulse = the unit impulse weighted by the value of the signal in 0: xn [ ] δ [
More informationFigure 1 A linear, time-invariant circuit. It s important to us that the circuit is both linear and time-invariant. To see why, let s us the notation
Convolution In this section we consider the problem of determining the response of a linear, time-invariant circuit to an arbitrary input, x(t). This situation is illustrated in Figure 1 where x(t) is
More informationx(t) = t[u(t 1) u(t 2)] + 1[u(t 2) u(t 3)]
ECE30 Summer II, 2006 Exam, Blue Version July 2, 2006 Name: Solution Score: 00/00 You must show all of your work for full credit. Calculators may NOT be used.. (5 points) x(t) = tu(t ) + ( t)u(t 2) u(t
More informationSignals and Systems Chapter 2
Signals and Systems Chapter 2 Continuous-Time Systems Prof. Yasser Mostafa Kadah Overview of Chapter 2 Systems and their classification Linear time-invariant systems System Concept Mathematical transformation
More informationECEN 420 LINEAR CONTROL SYSTEMS. Lecture 2 Laplace Transform I 1/52
1/52 ECEN 420 LINEAR CONTROL SYSTEMS Lecture 2 Laplace Transform I Linear Time Invariant Systems A general LTI system may be described by the linear constant coefficient differential equation: a n d n
More informationLaplace Transforms and use in Automatic Control
Laplace Transforms and use in Automatic Control P.S. Gandhi Mechanical Engineering IIT Bombay Acknowledgements: P.Santosh Krishna, SYSCON Recap Fourier series Fourier transform: aperiodic Convolution integral
More informationQuestion Paper Code : AEC11T02
Hall Ticket No Question Paper Code : AEC11T02 VARDHAMAN COLLEGE OF ENGINEERING (AUTONOMOUS) Affiliated to JNTUH, Hyderabad Four Year B. Tech III Semester Tutorial Question Bank 2013-14 (Regulations: VCE-R11)
More information2 Classification of Continuous-Time Systems
Continuous-Time Signals and Systems 1 Preliminaries Notation for a continuous-time signal: x(t) Notation: If x is the input to a system T and y the corresponding output, then we use one of the following
More informationLTI Systems (Continuous & Discrete) - Basics
LTI Systems (Continuous & Discrete) - Basics 1. A system with an input x(t) and output y(t) is described by the relation: y(t) = t. x(t). This system is (a) linear and time-invariant (b) linear and time-varying
More informationNAME: 23 February 2017 EE301 Signals and Systems Exam 1 Cover Sheet
NAME: 23 February 2017 EE301 Signals and Systems Exam 1 Cover Sheet Test Duration: 75 minutes Coverage: Chaps 1,2 Open Book but Closed Notes One 85 in x 11 in crib sheet Calculators NOT allowed DO NOT
More information信號與系統 Signals and Systems
Spring 2015 信號與系統 Signals and Systems Chapter SS-2 Linear Time-Invariant Systems Feng-Li Lian NTU-EE Feb15 Jun15 Figures and images used in these lecture notes are adopted from Signals & Systems by Alan
More information1.17 : Consider a continuous-time system with input x(t) and output y(t) related by y(t) = x( sin(t)).
(Note: here are the solution, only showing you the approach to solve the problems. If you find some typos or calculation error, please post it on Piazza and let us know ).7 : Consider a continuous-time
More informationChapter 1 Fundamental Concepts
Chapter 1 Fundamental Concepts 1 Signals A signal is a pattern of variation of a physical quantity, often as a function of time (but also space, distance, position, etc). These quantities are usually the
More informationProblem Value
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 30-Apr-04 COURSE: ECE-2025 NAME: GT #: LAST, FIRST Recitation Section: Circle the date & time when your Recitation
More informationENGIN 211, Engineering Math. Laplace Transforms
ENGIN 211, Engineering Math Laplace Transforms 1 Why Laplace Transform? Laplace transform converts a function in the time domain to its frequency domain. It is a powerful, systematic method in solving
More informationGATE 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 information4 The Continuous Time Fourier Transform
96 4 The Continuous Time ourier Transform ourier (or frequency domain) analysis turns out to be a tool of even greater usefulness Extension of ourier series representation to aperiodic signals oundation
More informationTime Response of Systems
Chapter 0 Time Response of Systems 0. Some Standard Time Responses Let us try to get some impulse time responses just by inspection: Poles F (s) f(t) s-plane Time response p =0 s p =0,p 2 =0 s 2 t p =
More informationEE 210. Signals and Systems Solutions of homework 2
EE 2. Signals and Systems Solutions of homework 2 Spring 2 Exercise Due Date Week of 22 nd Feb. Problems Q Compute and sketch the output y[n] of each discrete-time LTI system below with impulse response
More informationDEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2010
[E2.5] IMPERIAL COLLEGE LONDON DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2010 EEE/ISE PART II MEng. BEng and ACGI SIGNALS AND LINEAR SYSTEMS Time allowed: 2:00 hours There are FOUR
More informationDiscussion Section #2, 31 Jan 2014
Discussion Section #2, 31 Jan 2014 Lillian Ratliff 1 Unit Impulse The unit impulse (Dirac delta) has the following properties: { 0, t 0 δ(t) =, t = 0 ε ε δ(t) = 1 Remark 1. Important!: An ordinary function
More information1.4 Unit Step & Unit Impulse Functions
1.4 Unit Step & Unit Impulse Functions 1.4.1 The Discrete-Time Unit Impulse and Unit-Step Sequences Unit Impulse Function: δ n = ቊ 0, 1, n 0 n = 0 Figure 1.28: Discrete-time Unit Impulse (sample) 1 [n]
More informationEECE 3620: Linear Time-Invariant Systems: Chapter 2
EECE 3620: Linear Time-Invariant Systems: Chapter 2 Prof. K. Chandra ECE, UMASS Lowell September 7, 2016 1 Continuous Time Systems In the context of this course, a system can represent a simple or complex
More informationChapter 1 Fundamental Concepts
Chapter 1 Fundamental Concepts Signals A signal is a pattern of variation of a physical quantity as a function of time, space, distance, position, temperature, pressure, etc. These quantities are usually
More informationHomework 4. May An LTI system has an input, x(t) and output y(t) related through the equation y(t) = t e (t t ) x(t 2)dt
Homework 4 May 2017 1. An LTI system has an input, x(t) and output y(t) related through the equation y(t) = t e (t t ) x(t 2)dt Determine the impulse response of the system. Rewriting as y(t) = t e (t
More information4.1. If the input of the system consists of the superposition of M functions, M
4. The Zero-State Response: The system state refers to all information required at a point in time in order that a unique solution for the future output can be compute from the input. In the case of LTIC
More informationE2.5 Signals & Linear Systems. Tutorial Sheet 1 Introduction to Signals & Systems (Lectures 1 & 2)
E.5 Signals & Linear Systems Tutorial Sheet 1 Introduction to Signals & Systems (Lectures 1 & ) 1. Sketch each of the following continuous-time signals, specify if the signal is periodic/non-periodic,
More informationMAE143 A - Signals and Systems - Winter 11 Midterm, February 2nd
MAE43 A - Signals and Systems - Winter Midterm, February 2nd Instructions (i) This exam is open book. You may use whatever written materials you choose, including your class notes and textbook. You may
More informationCH.3 Continuous-Time Linear Time-Invariant System
CH.3 Continuous-Time Linear Time-Invariant System 1 LTI System Characterization 1.1 what does LTI mean? In Ch.2, the properties of the system are investigated. We are particularly interested in linear
More informationLaplace Transform Part 1: Introduction (I&N Chap 13)
Laplace Transform Part 1: Introduction (I&N Chap 13) Definition of the L.T. L.T. of Singularity Functions L.T. Pairs Properties of the L.T. Inverse L.T. Convolution IVT(initial value theorem) & FVT (final
More informationUniversity 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 informationGEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM. COURSE: ECE 3084A (Prof. Michaels)
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 30-Apr-14 COURSE: ECE 3084A (Prof. Michaels) NAME: STUDENT #: LAST, FIRST Write your name on the front page
More informationProfessor Fearing EECS120/Problem Set 2 v 1.01 Fall 2016 Due at 4 pm, Fri. Sep. 9 in HW box under stairs (1st floor Cory) Reading: O&W Ch 1, Ch2.
Professor Fearing EECS120/Problem Set 2 v 1.01 Fall 20 Due at 4 pm, Fri. Sep. 9 in HW box under stairs (1st floor Cory) Reading: O&W Ch 1, Ch2. Note: Π(t) = u(t + 1) u(t 1 ), and r(t) = tu(t) where u(t)
More informationModule 4. Related web links and videos. 1. FT and ZT
Module 4 Laplace transforms, ROC, rational systems, Z transform, properties of LT and ZT, rational functions, system properties from ROC, inverse transforms Related web links and videos Sl no Web link
More informationProblem Value
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 30-Apr-04 COURSE: ECE-2025 NAME: GT #: LAST, FIRST Recitation Section: Circle the date & time when your Recitation
More informationEC 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 informationUsing MATLAB with the Convolution Method
ECE 350 Linear Systems I MATLAB Tutorial #5 Using MATLAB with the Convolution Method A linear system with input, x(t), and output, y(t), can be described in terms of its impulse response, h(t). x(t) h(t)
More informationEE 3054: Signals, Systems, and Transforms Summer It is observed of some continuous-time LTI system that the input signal.
EE 34: Signals, Systems, and Transforms Summer 7 Test No notes, closed book. Show your work. Simplify your answers. 3. It is observed of some continuous-time LTI system that the input signal = 3 u(t) produces
More information信號與系統 Signals and Systems
Spring 2010 信號與系統 Signals and Systems Chapter SS-2 Linear Time-Invariant Systems Feng-Li Lian NTU-EE Feb10 Jun10 Figures and images used in these lecture notes are adopted from Signals & Systems by Alan
More informationNew Mexico State University Klipsch School of Electrical Engineering. EE312 - Signals and Systems I Spring 2018 Exam #1
New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Spring 2018 Exam #1 Name: Prob. 1 Prob. 2 Prob. 3 Prob. 4 Total / 30 points / 20 points / 25 points /
More information20.6. Transfer Functions. Introduction. Prerequisites. Learning Outcomes
Transfer Functions 2.6 Introduction In this Section we introduce the concept of a transfer function and then use this to obtain a Laplace transform model of a linear engineering system. (A linear engineering
More informationChapter 2: Linear systems & sinusoids OVE EDFORS DEPT. OF EIT, LUND UNIVERSITY
Chapter 2: Linear systems & sinusoids OVE EDFORS DEPT. OF EIT, LUND UNIVERSITY Learning outcomes After this lecture, the student should understand what a linear system is, including linearity conditions,
More information2.161 Signal Processing: Continuous and Discrete Fall 2008
MIT OpenCourseWare http://ocw.mit.edu.6 Signal Processing: Continuous and Discrete Fall 008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. MASSACHUSETTS
More informationCh 2: Linear Time-Invariant System
Ch 2: Linear Time-Invariant System A system is said to be Linear Time-Invariant (LTI) if it possesses the basic system properties of linearity and time-invariance. Consider a system with an output signal
More informationQUESTION BANK SIGNALS AND SYSTEMS (4 th SEM ECE)
QUESTION BANK SIGNALS AND SYSTEMS (4 th SEM ECE) 1. For the signal shown in Fig. 1, find x(2t + 3). i. Fig. 1 2. What is the classification of the systems? 3. What are the Dirichlet s conditions of Fourier
More information2. Time-Domain Analysis of Continuous- Time Signals and Systems
2. Time-Domain Analysis of Continuous- Time Signals and Systems 2.1. Continuous-Time Impulse Function (1.4.2) 2.2. Convolution Integral (2.2) 2.3. Continuous-Time Impulse Response (2.2) 2.4. Classification
More informationFrequency Response (III) Lecture 26:
EECS 20 N March 21, 2001 Lecture 26: Frequency Response (III) Laurent El Ghaoui 1 outline reading assignment: Chapter 8 of Lee and Varaiya we ll concentrate on continuous-time systems: convolution integral
More informatione st f (t) dt = e st tf(t) dt = L {t f(t)} s
Additional operational properties How to find the Laplace transform of a function f (t) that is multiplied by a monomial t n, the transform of a special type of integral, and the transform of a periodic
More informationProperties of LTI Systems
Properties of LTI Systems Properties of Continuous Time LTI Systems Systems with or without memory: A system is memory less if its output at any time depends only on the value of the input at that same
More informationEE 224 Signals and Systems I Review 1/10
EE 224 Signals and Systems I Review 1/10 Class Contents Signals and Systems Continuous-Time and Discrete-Time Time-Domain and Frequency Domain (all these dimensions are tightly coupled) SIGNALS SYSTEMS
More information1. SINGULARITY FUNCTIONS
1. SINGULARITY FUNCTIONS 1.0 INTRODUCTION Singularity functions are discontinuous functions or their derivatives are discontinuous. A singularity is a point at which a function does not possess a derivative.
More informationECE 301 Division 1 Exam 1 Solutions, 10/6/2011, 8-9:45pm in ME 1061.
ECE 301 Division 1 Exam 1 Solutions, 10/6/011, 8-9:45pm in ME 1061. Your ID will be checked during the exam. Please bring a No. pencil to fill out the answer sheet. This is a closed-book exam. No calculators
More informationCosc 3451 Signals and Systems. What is a system? Systems Terminology and Properties of Systems
Cosc 3451 Signals and Systems Systems Terminology and Properties of Systems What is a system? an entity that manipulates one or more signals to yield new signals (often to accomplish a function) can be
More informationGeneralized sources (Sect. 6.5). The Dirac delta generalized function. Definition Consider the sequence of functions for n 1, Remarks:
Generalized sources (Sect. 6.5). The Dirac delta generalized function. Definition Consider the sequence of functions for n, d n, t < δ n (t) = n, t 3 d3 d n, t > n. d t The Dirac delta generalized function
More informationFourier Transform for Continuous Functions
Fourier Transform for Continuous Functions Central goal: representing a signal by a set of orthogonal bases that are corresponding to frequencies or spectrum. Fourier series allows to find the spectrum
More informationECE 3620: Laplace Transforms: Chapter 3:
ECE 3620: Laplace Transforms: Chapter 3: 3.1-3.4 Prof. K. Chandra ECE, UMASS Lowell September 21, 2016 1 Analysis of LTI Systems in the Frequency Domain Thus far we have understood the relationship between
More information6.003 Homework #10 Solutions
6.3 Homework # Solutions Problems. DT Fourier Series Determine the Fourier Series coefficients for each of the following DT signals, which are periodic in N = 8. x [n] / n x [n] n x 3 [n] n x 4 [n] / n
More informationNAME: 13 February 2013 EE301 Signals and Systems Exam 1 Cover Sheet
NAME: February EE Signals and Systems Exam Cover Sheet Test Duration: 75 minutes. Coverage: Chaps., Open Book but Closed Notes. One 8.5 in. x in. crib sheet Calculators NOT allowed. This test contains
More informationIntroduction to Signals and Systems Lecture #4 - Input-output Representation of LTI Systems Guillaume Drion Academic year
Introduction to Signals and Systems Lecture #4 - Input-output Representation of LTI Systems Guillaume Drion Academic year 2017-2018 1 Outline Systems modeling: input/output approach of LTI systems. Convolution
More informationLINEAR SYSTEMS. J. Elder PSYC 6256 Principles of Neural Coding
LINEAR SYSTEMS Linear Systems 2 Neural coding and cognitive neuroscience in general concerns input-output relationships. Inputs Light intensity Pre-synaptic action potentials Number of items in display
More informationThis homework will not be collected or graded. It is intended to help you practice for the final exam. Solutions will be posted.
6.003 Homework #14 This homework will not be collected or graded. It is intended to help you practice for the final exam. Solutions will be posted. Problems 1. Neural signals The following figure illustrates
More information(t ) a 1. (t ).x 1..y 1
Introduction to the convolution Experiment # 4 LTI S ystems & Convolution Amongst the concepts that cause the most confusion to electrical engineering students, the Convolution Integral stands as a repeat
More informationSolution 10 July 2015 ECE301 Signals and Systems: Midterm. Cover Sheet
Solution 10 July 2015 ECE301 Signals and Systems: Midterm Cover Sheet Test Duration: 60 minutes Coverage: Chap. 1,2,3,4 One 8.5" x 11" crib sheet is allowed. Calculators, textbooks, notes are not allowed.
More informationModule 1: Signals & System
Module 1: Signals & System Lecture 6: Basic Signals in Detail Basic Signals in detail We now introduce formally some of the basic signals namely 1) The Unit Impulse function. 2) The Unit Step function
More information9.2 The Input-Output Description of a System
Lecture Notes on Control Systems/D. Ghose/212 22 9.2 The Input-Output Description of a System The input-output description of a system can be obtained by first defining a delta function, the representation
More informationModeling and Analysis of Systems Lecture #3 - Linear, Time-Invariant (LTI) Systems. Guillaume Drion Academic year
Modeling and Analysis of Systems Lecture #3 - Linear, Time-Invariant (LTI) Systems Guillaume Drion Academic year 2015-2016 1 Outline Systems modeling: input/output approach and LTI systems. Convolution
More informationCLTI System Response (4A) Young Won Lim 4/11/15
CLTI System Response (4A) Copyright (c) 2011-2015 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2
More informationEE102 Homework 2, 3, and 4 Solutions
EE12 Prof. S. Boyd EE12 Homework 2, 3, and 4 Solutions 7. Some convolution systems. Consider a convolution system, y(t) = + u(t τ)h(τ) dτ, where h is a function called the kernel or impulse response of
More informationSignals and Systems Lecture Notes
Dr. Mahmoud M. Al-Husari Signals and Systems Lecture Notes This set of lecture notes are never to be considered as a substitute to the textbook recommended by the lecturer. ii Contents Preface v 1 Introduction
More informationLecture 2 ELE 301: Signals and Systems
Lecture 2 ELE 301: Signals and Systems Prof. Paul Cuff Princeton University Fall 2011-12 Cuff (Lecture 2) ELE 301: Signals and Systems Fall 2011-12 1 / 70 Models of Continuous Time Signals Today s topics:
More informationLecture 6: Time-Domain Analysis of Continuous-Time Systems Dr.-Ing. Sudchai Boonto
Lecture 6: Time-Domain Analysis of Continuous-Time Systems Dr-Ing Sudchai Boonto Department of Control System and Instrumentation Engineering King Mongkut s Unniversity of Technology Thonburi Thailand
More informationConvolution and Linear Systems
CS 450: Introduction to Digital Signal and Image Processing Bryan Morse BYU Computer Science Introduction Analyzing Systems Goal: analyze a device that turns one signal into another. Notation: f (t) g(t)
More informationGrades will be determined by the correctness of your answers (explanations are not required).
6.00 (Fall 20) Final Examination December 9, 20 Name: Kerberos Username: Please circle your section number: Section Time 2 am pm 4 2 pm Grades will be determined by the correctness of your answers (explanations
More informationENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University
ENSC327 Communications Systems 2: Fourier Representations Jie Liang School of Engineering Science Simon Fraser University 1 Outline Chap 2.1 2.5: Signal Classifications Fourier Transform Dirac Delta Function
More informationBackground LTI Systems (4A) Young Won Lim 4/20/15
Background LTI Systems (4A) Copyright (c) 2014-2015 Young W. Lim. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2
More informationThe Continuous Time Fourier Transform
COMM 401: Signals & Systems Theory Lecture 8 The Continuous Time Fourier Transform Fourier Transform Continuous time CT signals Discrete time DT signals Aperiodic signals nonperiodic periodic signals Aperiodic
More informationECE 314 Signals and Systems Fall 2012
ECE 31 ignals and ystems Fall 01 olutions to Homework 5 Problem.51 Determine the impulse response of the system described by y(n) = x(n) + ax(n k). Replace x by δ to obtain the impulse response: h(n) =
More information2.161 Signal Processing: Continuous and Discrete Fall 2008
MIT OpenCourseWare http://ocw.mit.edu 2.161 Signal Processing: Continuous and Discrete Fall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts
More informationReview of Frequency Domain Fourier Series: Continuous periodic frequency components
Today we will review: Review of Frequency Domain Fourier series why we use it trig form & exponential form how to get coefficients for each form Eigenfunctions what they are how they relate to LTI systems
More informationChap 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 informationNew Mexico State University Klipsch School of Electrical Engineering. EE312 - Signals and Systems I Fall 2017 Exam #1
New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Fall 2017 Exam #1 Name: Prob. 1 Prob. 2 Prob. 3 Prob. 4 Total / 30 points / 20 points / 25 points / 25
More informationECE 3084 QUIZ 2 SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING GEORGIA INSTITUTE OF TECHNOLOGY APRIL 2, Name:
ECE 3084 QUIZ 2 SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING GEORGIA INSTITUTE OF TECHNOLOGY APRIL 2, 205 Name:. The quiz is closed book, except for one 2-sided sheet of handwritten notes. 2. Turn off
More informationLOPE3202: Communication Systems 10/18/2017 2
By Lecturer Ahmed Wael Academic Year 2017-2018 LOPE3202: Communication Systems 10/18/2017 We need tools to build any communication system. Mathematics is our premium tool to do work with signals and systems.
More informationNew Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Fall 2015 Final Exam
New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Fall 2015 Name: Solve problems 1 3 and two from problems 4 7. Circle below which two of problems 4 7 you
More information1 otherwise. Note that the area of the pulse is one. The Dirac delta function (a.k.a. the impulse) can be defined using the pulse as follows:
The Dirac delta function There is a function called the pulse: { if t > Π(t) = 2 otherwise. Note that the area of the pulse is one. The Dirac delta function (a.k.a. the impulse) can be defined using the
More informationBasic Procedures for Common Problems
Basic Procedures for Common Problems ECHE 550, Fall 2002 Steady State Multivariable Modeling and Control 1 Determine what variables are available to manipulate (inputs, u) and what variables are available
More informationECE 301 Fall 2011 Division 1 Homework 5 Solutions
ECE 301 Fall 2011 ivision 1 Homework 5 Solutions Reading: Sections 2.4, 3.1, and 3.2 in the textbook. Problem 1. Suppose system S is initially at rest and satisfies the following input-output difference
More informationInterconnection of LTI Systems
EENG226 Signals and Systems Chapter 2 Time-Domain Representations of Linear Time-Invariant Systems Interconnection of LTI Systems Prof. Dr. Hasan AMCA Electrical and Electronic Engineering Department (ee.emu.edu.tr)
More informationConvolution. Define a mathematical operation on discrete-time signals called convolution, represented by *. Given two discrete-time signals x 1, x 2,
Filters Filters So far: Sound signals, connection to Fourier Series, Introduction to Fourier Series and Transforms, Introduction to the FFT Today Filters Filters: Keep part of the signal we are interested
More information9.5 The Transfer Function
Lecture Notes on Control Systems/D. Ghose/2012 0 9.5 The Transfer Function Consider the n-th order linear, time-invariant dynamical system. dy a 0 y + a 1 dt + a d 2 y 2 dt + + a d n y 2 n dt b du 0u +
More informationChapter 6: The Laplace Transform. Chih-Wei Liu
Chapter 6: The Laplace Transform Chih-Wei Liu Outline Introduction The Laplace Transform The Unilateral Laplace Transform Properties of the Unilateral Laplace Transform Inversion of the Unilateral Laplace
More informationOrdinary differential equations
Class 11 We will address the following topics Convolution of functions Consider the following question: Suppose that u(t) has Laplace transform U(s), v(t) has Laplace transform V(s), what is the inverse
More informationThe Convolution Sum for Discrete-Time LTI Systems
The Convolution Sum for Discrete-Time LTI Systems Andrew W. H. House 01 June 004 1 The Basics of the Convolution Sum Consider a DT LTI system, L. x(n) L y(n) DT convolution is based on an earlier result
More informationDefinition of the Laplace transform. 0 x(t)e st dt
Definition of the Laplace transform Bilateral Laplace Transform: X(s) = x(t)e st dt Unilateral (or one-sided) Laplace Transform: X(s) = 0 x(t)e st dt ECE352 1 Definition of the Laplace transform (cont.)
More informationProblem Value
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL of ELECTRICAL & COMPUTER ENGINEERING FINAL EXAM DATE: 2-May-05 COURSE: ECE-2025 NAME: GT #: LAST, FIRST (ex: gtz123a) Recitation Section: Circle the date & time when
More informationChap 4. State-Space Solutions and
Chap 4. State-Space Solutions and Realizations Outlines 1. Introduction 2. Solution of LTI State Equation 3. Equivalent State Equations 4. Realizations 5. Solution of Linear Time-Varying (LTV) Equations
More informationUnit 2: Modeling in the Frequency Domain Part 2: The Laplace Transform. The Laplace Transform. The need for Laplace
Unit : Modeling in the Frequency Domain Part : Engineering 81: Control Systems I Faculty of Engineering & Applied Science Memorial University of Newfoundland January 1, 010 1 Pair Table Unit, Part : Unit,
More informationChapter 5 Frequency Domain Analysis of Systems
Chapter 5 Frequency Domain Analysis of Systems CT, LTI Systems Consider the following CT LTI system: xt () ht () yt () Assumption: the impulse response h(t) is absolutely integrable, i.e., ht ( ) dt< (this
More information