6.003 Homework #10 Solutions
|
|
- Ursula Wilkins
- 6 years ago
- Views:
Transcription
1 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 x [n] = sin n 4 = e j 4 e j 4 j = <N> a k e j N kn j k = a k = a k+8 = j k = k =,, 3, 4 b k = b k+8 = x[n]e j N kn N <N> = ( + e j k 4 + e j k e j 3k 4 e jk 5k j e 4 + 3k e j + ) 7k e j 4 8 c k = c k+8 = N x[n]e j N kn = <N> e j k 4 e j k 4 4 = j sin k 4 j 6 sin k j 3k sin e j k e j k + 3k e j 4 e j 3k 4 Because x 3 [n] is real-valued and an odd function of n, the series is purely imaginary. 8 x 4 [n] = x [n ] d k = d k+8 = e j j e j/4 k = N ak = d k = j e j/4 k = k =,, 3, 4
2 6.3 Homework # Solutions / Fall. Inverse DT Fourier Series Determine the DT signals with the following Fourier series coefficients. Assume that the signals are periodic in N = 8. / a k k b k k a k = cos k 4 = e jk 8 + e jk 8 x [n] = 4δ[n ] + 4δ[n + ] = N x[n]e j N kn <N> for n < 5. Since x [n] is periodic, a more general expression is x [n] = 4δ[n + 8k] + 4δ[n + + 8k] x [n] = k= k=<n> b k e j N kn = e j 8 n + e j 8 n Notice that x [n] has imaginary components, because the Fourier series coefficients are not conjugate symmetric (b k b k ).
3 6.3 Homework # Solutions / Fall 3 3. Impulsive Input Let the following periodic signal x(t) = δ(t 3m) + δ(t 3m) δ(t 3m) m= be the input to an LTI system with system function H(s) = e s/4 e s/4. Let b k represent the Fourier series coefficients of the resulting output signal y(t). Determine b 3. The period of x(t) is T = 3. Therefore the period of y(t) is also T = 3. The fundamental frequency of x(t) (and y(t)) is = T = 3. Let a k represent the Fourier series coefficients for x(t). Then a k = 3 (δ(t) + δ(t ) δ(t )) e j 3 kt dt = ( + e j 3 k e j k) a 3 = 3 The frequency response of the system is given by Therefore H(j) = e j/4 e j/4 = j sin 4 b k = H (j 3 ) ( k a k = j sin k ) a k and b 3 = ( j sin ) 3 = j 3.
4 6.3 Homework # Solutions / Fall 4 4. Fourier transform Part a. Find the Fourier transform of x (t) = e t. X (j) = = = e t e jt dt = e ( j)t dt + j j = + Part b. Find the Fourier transform of x (t) = + t. Hint: Try duality. By duality, if then Therefore e t + + t e X (j) = e e t e jt dt + e ( j)t dt = e( j)t j e t e jt dt + e( j)t j We can check this result by inverse transforming X (j): x (t) = = e e jt d = e (+jt) d + = + jt + jt = + t e e jt d + e ( +jt) d = e (+jt) + jt e e jt d + e ( +jt) + jt
5 6.3 Homework # Solutions / Fall 5 5. Fourier transform Part a. Determine x (t), whose Fourier transform X (j) has the following magnitude and angle. X (j) 9 X (j) / / Express x (t) as a closed-form and sketch this function of time. X (j) = X (j) e j X (j) = { 3j < otherwise Notice that X (j) is 3j times X a (j) defined as { X a (j) = < otherwise Thus x (t) = 3 d dt x a(t) where Thus x a (t) = sin t t. x (t) = 3 (t cos t sin t) t t Part b. Determine x (t), whose Fourier transform X (j) has the following magnitude and angle. X (j) 9 X (j) / /
6 6.3 Homework # Solutions / Fall 6 Express x (t) as a closed-form and sketch this function of time. X (j) can be expressed as a difference: 9 9 Thus sin t x (t) = 9 6 sin t t t t Part c. What are important similarities and differences between x (t) and x (t)? How do those similarities and differences manifest in their Fourier transforms? Both x (t) and x (t) are real functions of time. However, x (t) is an odd function of time and x (t) is an even function of time. Taken together, these features mean that X (j) is an odd function of that is purely imaginary, and X () is an even function of that is purely real. Both X (j) and X (j) are zero for >. infinite extents in time. Therefore, both x ( t) and x (t) have Both X (j) and X (j) are discontinuous functions of. Thus, the magnitudes of x (t) and x (t) both decrease as t for large t.
7 6.3 Homework # Solutions / Fall 7 6. Fourier Transforms The magnitude and angle of the Fourier transform of a signal x(t) are given in the following plots. X(j) X(j) Five signals are derived from x(t) as shown in the left column of the following table. Six magnitude plots (M-M6) and six angle plots (A-A6) are shown on the next page. Determine which of these plots is associated with each of the derived signals and place the appropriate label (e.g., M or A3) in the following table. Note that more than one derived signal could have the same magnitude or angle. signal magnitude angle dx(t) dt (x x)(t) ( x t ) x(t) x (t) M5 M3 M M4 M6 A4 A A A3 A
8 6.3 Homework # Solutions / Fall 8 M A M A M3 A3 M4 A4 M5 A5 4 M6 A6
Ch 4: The Continuous-Time Fourier Transform
Ch 4: The Continuous-Time Fourier Transform Fourier Transform of x(t) Inverse Fourier Transform jt X ( j) x ( t ) e dt jt x ( t ) X ( j) e d 2 Ghulam Muhammad, King Saud University Continuous-time aperiodic
More informationThe Continuous-time Fourier
The Continuous-time Fourier Transform Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline Representation of Aperiodic signals:
More information3 Fourier Series Representation of Periodic Signals
65 66 3 Fourier Series Representation of Periodic Signals Fourier (or frequency domain) analysis constitutes a tool of great usefulness Accomplishes decomposition of broad classes of signals using complex
More informationECE 301: Signals and Systems Homework Assignment #5
ECE 30: Signals and Systems Homework Assignment #5 Due on November, 205 Professor: Aly El Gamal TA: Xianglun Mao Aly El Gamal ECE 30: Signals and Systems Homework Assignment #5 Problem Problem Compute
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 informationThe Discrete-time Fourier Transform
The Discrete-time Fourier Transform Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline Representation of Aperiodic signals: The
More informationFourier Series Representation of
Fourier Series Representation of Periodic Signals Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline The response of LIT system
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 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 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 informationContinuous-Time Fourier Transform
Signals and Systems Continuous-Time Fourier Transform Chang-Su Kim continuous time discrete time periodic (series) CTFS DTFS aperiodic (transform) CTFT DTFT Lowpass Filtering Blurring or Smoothing Original
More informationGrades will be determined by the correctness of your answers (explanations are not required).
6.00 (Fall 2011) Final Examination December 19, 2011 Name: Kerberos Username: Please circle your section number: Section Time 2 11 am 1 pm 4 2 pm Grades will be determined by the correctness of your answers
More 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 informationThe Johns Hopkins University Department of Electrical and Computer Engineering Introduction to Linear Systems Fall 2002.
The Johns Hopkins University Department of Electrical and Computer Engineering 505.460 Introduction to Linear Systems Fall 2002 Final exam Name: You are allowed to use: 1. Table 3.1 (page 206) & Table
More information3.2 Complex Sinusoids and Frequency Response of LTI Systems
3. Introduction. A signal can be represented as a weighted superposition of complex sinusoids. x(t) or x[n]. LTI system: LTI System Output = A weighted superposition of the system response to each complex
More informationECE 350 Signals and Systems Spring 2011 Final Exam - Solutions. Three 8 ½ x 11 sheets of notes, and a calculator are allowed during the exam.
ECE 35 Spring - Final Exam 9 May ECE 35 Signals and Systems Spring Final Exam - Solutions Three 8 ½ x sheets of notes, and a calculator are allowed during the exam Write all answers neatly and show your
More 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 informationTopic 3: Fourier Series (FS)
ELEC264: Signals And Systems Topic 3: Fourier Series (FS) o o o o Introduction to frequency analysis of signals CT FS Fourier series of CT periodic signals Signal Symmetry and CT Fourier Series Properties
More informationModule 4 : Laplace and Z Transform Problem Set 4
Module 4 : Laplace and Z Transform Problem Set 4 Problem 1 The input x(t) and output y(t) of a causal LTI system are related to the block diagram representation shown in the figure. (a) Determine a differential
More informationECE 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 informationSignals & Systems. Lecture 5 Continuous-Time Fourier Transform. Alp Ertürk
Signals & Systems Lecture 5 Continuous-Time Fourier Transform Alp Ertürk alp.erturk@kocaeli.edu.tr Fourier Series Representation of Continuous-Time Periodic Signals Synthesis equation: x t = a k e jkω
More informationComplex 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 informationECE 308 SIGNALS AND SYSTEMS SPRING 2013 Examination #2 14 March 2013
ECE 308 SIGNALS AND SYSTEMS SPRING 2013 Examination #2 14 March 2013 Name: Instructions: The examination lasts for 75 minutes and is closed book, closed notes. No electronic devices are permitted, including
More informationHomework 7 Solution EE235, Spring Find the Fourier transform of the following signals using tables: te t u(t) h(t) = sin(2πt)e t u(t) (2)
Homework 7 Solution EE35, Spring. Find the Fourier transform of the following signals using tables: (a) te t u(t) h(t) H(jω) te t u(t) ( + jω) (b) sin(πt)e t u(t) h(t) sin(πt)e t u(t) () h(t) ( ejπt e
More informationFourier series for continuous and discrete time signals
8-9 Signals and Systems Fall 5 Fourier series for continuous and discrete time signals The road to Fourier : Two weeks ago you saw that if we give a complex exponential as an input to a system, the output
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 informationSignals & Systems. Lecture 4 Fourier Series Properties & Discrete-Time Fourier Series. Alp Ertürk
Signals & Systems Lecture 4 Fourier Series Properties & Discrete-Time Fourier Series Alp Ertürk alp.erturk@kocaeli.edu.tr Fourier Series Representation of Continuous-Time Periodic Signals Synthesis equation:
More informationTable 1: Properties of the Continuous-Time Fourier Series. Property Periodic Signal Fourier Series Coefficients
able : Properties of the Continuous-ime Fourier Series x(t = e jkω0t = = x(te jkω0t dt = e jk(/t x(te jk(/t dt Property Periodic Signal Fourier Series Coefficients x(t y(t } Periodic with period and fundamental
More informationDiscrete-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 informationECE-314 Fall 2012 Review Questions for Midterm Examination II
ECE-314 Fall 2012 Review Questions for Midterm Examination II First, make sure you study all the problems and their solutions from homework sets 4-7. Then work on the following additional problems. Problem
More informationEECS20n, Solution to Mock Midterm 2, 11/17/00
EECS20n, Solution to Mock Midterm 2, /7/00. 5 points Write the following in Cartesian coordinates (i.e. in the form x + jy) (a) point j 3 j 2 + j =0 (b) 2 points k=0 e jkπ/6 = ej2π/6 =0 e jπ/6 (c) 2 points(
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 information06/12/ rws/jMc- modif SuFY10 (MPF) - Textbook Section IX 1
IV. Continuous-Time Signals & LTI Systems [p. 3] Analog signal definition [p. 4] Periodic signal [p. 5] One-sided signal [p. 6] Finite length signal [p. 7] Impulse function [p. 9] Sampling property [p.11]
More 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 informationCH.4 Continuous-Time Fourier Series
CH.4 Continuous-Time Fourier Series First step to Fourier analysis. My mathematical model is killing me! The difference between mathematicians and engineers is mathematicians develop mathematical tools
More informationRepresenting a Signal
The Fourier Series Representing a Signal The convolution method for finding the response of a system to an excitation takes advantage of the linearity and timeinvariance of the system and represents the
More informationTable 1: Properties of the Continuous-Time Fourier Series. Property Periodic Signal Fourier Series Coefficients
able : Properties of the Continuous-ime Fourier Series x(t = a k e jkω0t = a k = x(te jkω0t dt = a k e jk(/t x(te jk(/t dt Property Periodic Signal Fourier Series Coefficients x(t y(t } Periodic with period
More informationEE Homework 12 - Solutions. 1. The transfer function of the system is given to be H(s) = s j j
EE3054 - Homework 2 - Solutions. The transfer function of the system is given to be H(s) = s 2 +3s+3. Decomposing into partial fractions, H(s) = 0.5774j s +.5 0.866j + 0.5774j s +.5 + 0.866j. () (a) The
More informationECE 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 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 informationFinal Exam of ECE301, Section 3 (CRN ) 8 10am, Wednesday, December 13, 2017, Hiler Thtr.
Final Exam of ECE301, Section 3 (CRN 17101-003) 8 10am, Wednesday, December 13, 2017, Hiler Thtr. 1. Please make sure that it is your name printed on the exam booklet. Enter your student ID number, and
More informationFinal Exam 14 May LAST Name FIRST Name Lab Time
EECS 20n: Structure and Interpretation of Signals and Systems Department of Electrical Engineering and Computer Sciences UNIVERSITY OF CALIFORNIA BERKELEY Final Exam 14 May 2005 LAST Name FIRST Name Lab
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 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 informationECE 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 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 informationFrequency Response and Continuous-time Fourier Series
Frequency Response and Continuous-time Fourier Series Recall course objectives Main Course Objective: Fundamentals of systems/signals interaction (we d like to understand how systems transform or affect
More informationAssignment 4 Solutions Continuous-Time Fourier Transform
Assignment 4 Solutions Continuous-Time Fourier Transform ECE 3 Signals and Systems II Version 1.01 Spring 006 1. Properties of complex numbers. Let c 1 α 1 + jβ 1 and c α + jβ be two complex numbers. a.
More informationIntroduction to DFT. Deployment of Telecommunication Infrastructures. Azadeh Faridi DTIC UPF, Spring 2009
Introduction to DFT Deployment of Telecommunication Infrastructures Azadeh Faridi DTIC UPF, Spring 2009 1 Review of Fourier Transform Many signals can be represented by a fourier integral of the following
More information信號與系統 Signals and Systems
Spring 2011 信號與系統 Signals and Systems Chapter SS-4 The Continuous-Time Fourier Transform Feng-Li Lian NTU-EE Feb11 Jun11 Figures and images used in these lecture notes are adopted from Signals & Systems
More informationDSP Laboratory (EELE 4110) Lab#5 DTFS & DTFT
Islamic University of Gaza Faculty of Engineering Electrical Engineering Department EG.MOHAMMED ELASMER Spring-22 DSP Laboratory (EELE 4) Lab#5 DTFS & DTFT Discrete-Time Fourier Series (DTFS) The discrete-time
More information3. Frequency-Domain Analysis of Continuous- Time Signals and Systems
3. Frequency-Domain Analysis of Continuous- ime Signals and Systems 3.. Definition of Continuous-ime Fourier Series (3.3-3.4) 3.2. Properties of Continuous-ime Fourier Series (3.5) 3.3. Definition of Continuous-ime
More informationHomework 9 Solutions
8-290 Signals and Systems Profs. Byron Yu and Pulkit Grover Fall 207 Homework 9 Solutions Part One. (6 points) Compute the convolution of the following continuous-time aperiodic signals. (Hint: Use the
More informationDigital Signal Processing. Midterm 1 Solution
EE 123 University of California, Berkeley Anant Sahai February 15, 27 Digital Signal Processing Instructions Midterm 1 Solution Total time allowed for the exam is 8 minutes Some useful formulas: Discrete
More 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 informationGeorge Mason University Signals and Systems I Spring 2016
George Mason University Signals and Systems I Spring 206 Problem Set #6 Assigned: March, 206 Due Date: March 5, 206 Reading: This problem set is on Fourier series representations of periodic signals. The
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 informationFinal 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 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 informationBridge between continuous time and discrete time signals
6 Sampling Bridge between continuous time and discrete time signals Sampling theorem complete representation of a continuous time signal by its samples Samplingandreconstruction implementcontinuous timesystems
More informationDigital 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 informationENSC327 Communications Systems 2: Fourier Representations. School of Engineering Science Simon Fraser University
ENSC37 Communications Systems : Fourier Representations School o Engineering Science Simon Fraser University Outline Chap..5: Signal Classiications Fourier Transorm Dirac Delta Function Unit Impulse Fourier
More informationChapter 3 Fourier Representations of Signals and Linear Time-Invariant Systems
Chapter 3 Fourier Representations of Signals and Linear Time-Invariant Systems Introduction Complex Sinusoids and Frequency Response of LTI Systems. Fourier Representations for Four Classes of Signals
More informationUniversity of Connecticut Lecture Notes for ME5507 Fall 2014 Engineering Analysis I Part III: Fourier Analysis
University of Connecticut Lecture Notes for ME557 Fall 24 Engineering Analysis I Part III: Fourier Analysis Xu Chen Assistant Professor United Technologies Engineering Build, Rm. 382 Department of Mechanical
More informationDiscrete-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 informationSignals 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 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 informationDiscrete 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 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 informationEach problem is worth 25 points, and you may solve the problems in any order.
EE 120: Signals & Systems Department of Electrical Engineering and Computer Sciences University of California, Berkeley Midterm Exam #2 April 11, 2016, 2:10-4:00pm Instructions: There are four questions
More 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 informationFourier transform representation of CT aperiodic signals Section 4.1
Fourier transform representation of CT aperiodic signals Section 4. A large class of aperiodic CT signals can be represented by the CT Fourier transform (CTFT). The (CT) Fourier transform (or spectrum)
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 informationEE Homework 13 - Solutions
EE3054 - Homework 3 - Solutions. (a) The Laplace transform of e t u(t) is s+. The pole of the Laplace transform is at which lies in the left half plane. Hence, the Fourier transform is simply the Laplace
More informationso mathematically we can say that x d [n] is a discrete-time signal. The output of the DT system is also discrete, denoted by y d [n].
ELEC 36 LECURE NOES WEEK 9: Chapters 7&9 Chapter 7 (cont d) Discrete-ime Processing of Continuous-ime Signals It is often advantageous to convert a continuous-time signal into a discrete-time signal so
More informationExamples of the Fourier Theorem (Sect. 10.3). The Fourier Theorem: Continuous case.
s of the Fourier Theorem (Sect. 1.3. The Fourier Theorem: Continuous case. : Using the Fourier Theorem. The Fourier Theorem: Piecewise continuous case. : Using the Fourier Theorem. The Fourier Theorem:
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 informationThe different frequency components in a sound signal are processed first by the sensory system in the ear then some specialized cortical areas in the
Signals Represented in Terms of Magnitude Phase The physical interpretation of the Fourier transform of a time signal is its decomposition into a linear combination of frequency components with different
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 information12/20/2017. Lectures on Signals & systems Engineering. Designed and Presented by Dr. Ayman Elshenawy Elsefy
//7 ectures on Signals & systems Engineering Designed and Presented by Dr. Ayman Elshenawy Elsefy Dept. of Systems & Computer Eng. Al-Azhar University Email : eaymanelshenawy@yahoo.com aplace Transform
More informationSignals and Systems Spring 2004 Lecture #9
Signals and Systems Spring 2004 Lecture #9 (3/4/04). The convolution Property of the CTFT 2. Frequency Response and LTI Systems Revisited 3. Multiplication Property and Parseval s Relation 4. The DT Fourier
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 informationIdentification Methods for Structural Systems. Prof. Dr. Eleni Chatzi System Stability - 26 March, 2014
Prof. Dr. Eleni Chatzi System Stability - 26 March, 24 Fundamentals Overview System Stability Assume given a dynamic system with input u(t) and output x(t). The stability property of a dynamic system can
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 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 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 informationOn the Stability of Linear Systems
On the Stability of Linear Systems by Daniele Sasso * Abstract The criteria of stability defined in the standard theory of linear systems aren t exhaustive and show some inconsistencies. In this article
More informationReview of Discrete-Time System
Review of Discrete-Time System Electrical & Computer Engineering University of Maryland, College Park Acknowledgment: ENEE630 slides were based on class notes developed by Profs. K.J. Ray Liu and Min Wu.
More informationFOURIER TRANSFORMS. At, is sometimes taken as 0.5 or it may not have any specific value. Shifting at
Chapter 2 FOURIER TRANSFORMS 2.1 Introduction The Fourier series expresses any periodic function into a sum of sinusoids. The Fourier transform is the extension of this idea to non-periodic functions by
More informationECE 301: Signals and Systems Homework Assignment #3
ECE 31: Signals and Systems Homework Assignment #3 Due on October 14, 215 Professor: Aly El Gamal A: Xianglun Mao 1 Aly El Gamal ECE 31: Signals and Systems Homework Assignment #3 Problem 1 Problem 1 Consider
More information5.1 The Discrete Time Fourier Transform
32 33 5 The Discrete Time ourier Transform ourier (or frequency domain) analysis the last Complete the introduction and the development of the methods of ourier analysis Learn frequency-domain methods
More information8 Continuous-Time Fourier Transform
8 Continuous-Time Fourier Transform Recommended Problems P8. Consider the signal x(t), which consists of a single rectangular pulse of unit height, is symmetric about the origin, and has a total width
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 informationContinuous-time Fourier Methods
ELEC 321-001 SIGNALS and SYSTEMS Continuous-time Fourier Methods Chapter 6 1 Representing a Signal The convolution method for finding the response of a system to an excitation takes advantage of the linearity
More informationHomework 3 (Stochastic Processes)
In the name of GOD. Sharif University of Technology Stochastic Processes CE 695 Dr. H.R. Rabiee Homework 3 (Stochastic Processes). Explain why each of the following is NOT a valid autocorrrelation function:
More informationEEL3135: 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 informationLine Spectra and their Applications
In [ ]: cd matlab pwd Line Spectra and their Applications Scope and Background Reading This session concludes our introduction to Fourier Series. Last time (http://nbviewer.jupyter.org/github/cpjobling/eg-47-
More informationGeneration of bandlimited sync transitions for sine waveforms
Generation of bandlimited sync transitions for sine waveforms Vadim Zavalishin May 4, 9 Abstract A common way to generate bandlimited sync transitions for the classical analog waveforms is the BLEP method.
More informationNAME: ht () 1 2π. Hj0 ( ) dω Find the value of BW for the system having the following impulse response.
University of California at Berkeley Department of Electrical Engineering and Computer Sciences Professor J. M. Kahn, EECS 120, Fall 1998 Final Examination, Wednesday, December 16, 1998, 5-8 pm NAME: 1.
More informationSolution 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