DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2008

Size: px
Start display at page:

Download "DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2008"

Transcription

1 [E5] IMPERIAL COLLEGE LONDON DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 008 EEE/ISE PART II MEng BEng and ACGI SIGNALS AND LINEAR SYSTEMS Time allowed: :00 hours There are FOUR quesions on his paper Q is compulsory Answer Q and any wo of quesions -4 Q carries 40% of he marks Quesions o 4 carry equal marks (30% each) Any special insrucions for invigilaors and informaion for candidaes are on page Firs Marker: Second Marker: Peer Y K Cheung M M Draief

2 [E5] Special insrucions for invigilaors: None Informaion for candidaes: None Page of 7

3 [E5] [Quesion is compulsory] a) Wih a single equaion, define he characerisic of a linear sysem j b) Find he even and odd componens of he signal x () = e θ [] [] c) A coninuous-ime signal x () is shown in Figure Skech he signals i) x ()[ u () u ( )] ii) 3 x () δ ( ) [3] [3] Figure d) Consider he RC circui shown in Figure Find he relaionship beween he inpu x () = v() and he oupu y () = i () in he form of: s i) a differenial equaion; [3] ii) a ransfer funcion [3] R + + v s () i() C V c () Figure 3 e) The uni impulse response of an LTI sysem is h () = e e u () Find he sysem s zero-sae response y () if he inpu x () = e u () Noe ha e e () () = () for λ λ λ λ λ λ λ λ e u e u u Page 3 of 7

4 [E5] f) Using he graphical mehod, find y () = x () h () where x () and h () are shown in Figure 3 Figure 3 g) Find he pole and zero locaions for a n sysem wih he ransfer funcion s s+ 5/ H() s = s + 5s+ 4 h) Given ha he Fourier ransform of he signal x () is X ( ω ), ie x () Xω ( ), prove from firs principle ha x e X jω0 ( 0) ( ω) i) Using he z-ransform pairs uk [ ] z k z and γ uk [ ] z z γ inverse z-ransform of zz ( 7) Fz [ ] = z 5z+ 4 j) A TV signal has a bandwidh of 45 MHz This signal is sampled and quanized wih an analogue-o-digial converer i) Deermine he sampling rae if he signal is o be sampled a a rae 0% above he Nyquis rae [] ii) If he samples are quanized ino 04 levels, deermine he bi-rae (ie bis/second) of he binary coded signal [] Page 4 of 7

5 [E5] a) Given he iniial condiions y (0) = 0 and y (0) = 0 0, find he uni impulse response of an LTI sysem specified by he equaion d y dy dx y ( ) = + 9 x ( ) d d d [5] b) An inpu signal f() is expressed in erms of sep componens as shown in Figure The sep componen a ime = τ has a heigh of Δ f which can be expressed as Δf Δ f = Δ τ = f ( τ) Δτ Δτ If g () is he uni sep response of an LTI sysem o he sep inpu u (), show ha he zero-sae response y () of he sysem o he inpu f() can be expressed as y () = f ( τ) g ( τ) dτ = f () g () [5] f() df dτ Δτ τ = nδτ Figure Page 5 of 7

6 [E5] 3 a) Find he Fourier ransform of he signal shown in Figure 3 using wo differen mehods: i) By direc inegraion using he definiion of he Fourier ransform [0] ii) Using only he ime-shifing propery and he Fourier ransform pair rec τ sinc ωτ τ [0] b) Given ha x / e dx= π, show ha he energy f E of a Gaussian pulse f() = e σ σ π is given by E f = σ π You should derive he energy E f from F( ω ) using he Parseval s heorem and he following Fourier ransform pair e / σ σ ω / σ π e [0] Figure 3 Page 6 of 7

7 [E5] 4 A discree-ime LTI sysem is specified by he difference equaion yk [ + ] 05 yk [ ] = f[ k+ ] + 08 f[ k] a) Derive is ransfer funcion in he z-domain [6] b) Find he ampliude and phase response of he sysem π c) Find he sysem response yk [ ] for he inpu f[ k] = cos(05 k ) 3 [0] [THE END] Page 7 of 7

8

9 E5 Signals and Linear Sysems Soluions 008 All quesions are unseen Quesion is compulsory Answer o Quesion a) If x y and x y, for a linear sysem, kx + kx ky + k y where k and k are consans [] b) Therefore, Even: cosθ Odd: j sinθ j x () = e θ = cosθ + jsinθ [] c) i) ii) [3] [3] Page of 7

10 d) i) v () = Ri() + v () s vc () = i( τ) dτ C x () = v(), y () = i () s Ry() + y( τ) dτ = x () C c Differeniae boh sides wr : dy dx R + y () = d C d dy dx + y () = d RC R d ii) Take Laplace ransform on boh sides: ( s+ ) Y() s = sx() s RC R [3] Y() s s H() s = = C X() s RCs+ [3] e) y () = h () x () 3 = ( e e ) u( ) e u( ) 3 = e u( ) e u( ) e u( ) e u( ) 3 ( e e ) ( e e ) = u () = e e u() 3 ( ) f) Page of 7

11 g) The complex zeros are given by: z z+ = 0 Therefore he zeros are a: ± -0 3 z= = ± j The poles are given by: p + 5p+ 5 = ( p+ 4)( p+ ) = 0 Therefore he poles are a: p = and p = 4 5 h) By definiion of Fourier ransform, Le τ = 0, jω FT of x ( ) = x ( ) e d 0 0 jω jωτ ( + 0 ) x ( 0) e d= x( τ) e d jω0 jωτ jω0 τ = e x( τ) e dτ = e X( ω) i) Divide F[z] by z, and perform parial fracion: Fz [ ] z 7 z 7 = = = z z 5z+ 4 ( z )( z 4) z z 4 z z Fz [ ] = z z 4 k f[ k] = [ 4 ] u[ k] j) 6 i) Nyquis rae is 45 0 = 9 MHz Therefore he acual sampling rae = 9 MHz =08 MHz ii) 04 levels require 0 bis per sample Therefore bi-rae is: = 08 Mbis/sec [] [] Page 3 of 7

12 Answer o Quesion Express he differenial equaion in erms of D operaors: ( D + 6D+ 9) y() = (D+ 9) x() Q( D) y() = P( D) x() QD D D PD D ( ) = ( ), ( ) = ( + 9) The characerisic equaion is herefore: ( λ + 6λ+ 9) = 0 ( λ+ 3) = 0 y ( ) = ( c + c ) e and y ( ) = [ 3( c + c ) + c ] e Seing = 0, and subsiuing 3 e y0 y 0 (0) = 0 and (0) =, gives 0= c c = 0 = 3c+ c c = y ( ) = e and y ( ) = ( 3+ ) e Now he impulse response can be calculaed: h () = [ PD ( ) y()] u () 0 = [ y ( ) + 9 y ( )] u( ) 0 0 = ( 6e e 9 e ) u( ) = + 3 ( 3 e ) u ( ) [5] a) The sysem response o u () is g (), and he response o he sep u ( τ ) is g ( τ ) (ime-invarian propery) Δf I is given ha Δ f = Δ τ = f ( τ) Δτ The sep componen a = nδ τ herefore has a Δτ heigh of f ( nδτ) Δτ, and can be expressed as f ( n τ ) τ Δ Δ u ( nδτ ) This gives a response Δ y () a he oupu, where Δ y () = f ( nδτ) Δτ g ( nδτ) Therefore, he oal response due o ALL sep componens is: y () = lim f ( nδτ) g ( nδτ) Δτ Δτ 0 n = = f ( τ) g( τ) dτ = f ( τ) g( τ) = f () g() [5] Page 4 of 7

13 Answer o Quesion 3 a) i) From definiion of Fourier ransform, jω F( ω) = f( ) e d 0 τ jω jω e d e d τ 0 = jω = e e jω jω 0 τ τ jω 0 jω jω = + e + e jω jω jω jω = + cos ωτ jω jω 4 sin ωτ = j ω ii) Express f() as sum of wo recangular funcions: + τ / τ / f () = rec rec τ τ Given ha rec ωτ τ sinc τ, apply ime-shifing propery gives Therefore ± τ / ωτ rec τ sinc τ ± j / e ωτ ωτ ωτ F( ω) = τ sinc e τ sinc e ωτ ωτ = j τ sinc sin 4 sin ωτ = j ω + jωτ / jωτ / [0] [0] Page 5 of 7

14 b) and f() = e σ σ π e σ π σ / e σ ω Parseval s Theorem saes: Given we obain: Ef = F( ω) dω π F( ω) = / e σ ω Ef e d π σ ω = ω x x Le σω =, hen σ ω = and dω = dx σ Therefore Ef = e dx= π σ σ π x / [0] Page 6 of 7

15 Answer o Quesion 4 a) Taking z-ransform of boh sides: zyz [ ] 05 Yz [ ] = zfz [ ] + 08 Fz [ ] Therefore Yz [ ] z+ 08 Hz [ ] = = Fz [ ] z 05 b) The frequency response is given by: jω jω e + 08 (cos Ω+ 08) + jsin Ω He [ ] = = jω e 05 (cosω 05) + jsin Ω Therefore, he ampliude response is jω jω jω He [ ] = He [ ] He [ ] jω jω ( e + 08)( e + 08) = jω jω ( e 05)( e 05) cosΩ = 5 cosω The phase response is j sin sin He [ Ω ] an Ω an Ω = cosω+ 08 cosω 05 π c) Since f[ k] = cos(05 k ), Ω= 05 3 Therefore j cos 05 He [ Ω ] = = cos 05 j He [ Ω ] = 86 j sin 05 sin 05 He [ Ω ] an an = cos cos05 05 = = 0653 radian or 3583 Therfore, he sysem response is π yk [ ] = 86 cos(05k 0653) = 86 cos(05k 675) 3 Page 7 of 7

16

ENGI 9420 Engineering Analysis Assignment 2 Solutions

ENGI 9420 Engineering Analysis Assignment 2 Solutions ENGI 940 Engineering Analysis Assignmen Soluions 0 Fall [Second order ODEs, Laplace ransforms; Secions.0-.09]. Use Laplace ransforms o solve he iniial value problem [0] dy y, y( 0) 4 d + [This was Quesion

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

EE 224 Signals and Systems I Complex numbers sinusodal signals Complex exponentials e jωt phasor addition

EE 224 Signals and Systems I Complex numbers sinusodal signals Complex exponentials e jωt phasor addition EE 224 Signals and Sysems I Complex numbers sinusodal signals Complex exponenials e jω phasor addiion 1/28 Complex Numbers Recangular Polar y z r z θ x Good for addiion/subracion Good for muliplicaion/division

More information

Q1) [20 points] answer for the following questions (ON THIS SHEET):

Q1) [20 points] answer for the following questions (ON THIS SHEET): Dr. Anas Al Tarabsheh The Hashemie Universiy Elecrical and Compuer Engineering Deparmen (Makeup Exam) Signals and Sysems Firs Semeser 011/01 Final Exam Dae: 1/06/01 Exam Duraion: hours Noe: means convoluion

More information

Chapter 1 Fundamental Concepts

Chapter 1 Fundamental Concepts Chaper 1 Fundamenal Conceps 1 Signals A signal is a paern of variaion of a physical quaniy, ofen as a funcion of ime (bu also space, disance, posiion, ec). These quaniies are usually he independen variables

More information

Voltage/current relationship Stored Energy. RL / RC circuits Steady State / Transient response Natural / Step response

Voltage/current relationship Stored Energy. RL / RC circuits Steady State / Transient response Natural / Step response Review Capaciors/Inducors Volage/curren relaionship Sored Energy s Order Circuis RL / RC circuis Seady Sae / Transien response Naural / Sep response EE4 Summer 5: Lecure 5 Insrucor: Ocavian Florescu Lecure

More information

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires

More information

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 1 Solutions

Signals and Systems Profs. Byron Yu and Pulkit Grover Fall Midterm 1 Solutions 8-90 Signals and Sysems Profs. Byron Yu and Pulki Grover Fall 07 Miderm Soluions Name: Andrew ID: Problem Score Max 0 8 4 6 5 0 6 0 7 8 9 0 6 Toal 00 Miderm Soluions. (0 poins) Deermine wheher he following

More information

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0. Time-Domain Sysem Analysis Coninuous Time. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 1. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 2 Le a sysem be described by a 2 y ( ) + a 1

More information

5. Response of Linear Time-Invariant Systems to Random Inputs

5. Response of Linear Time-Invariant Systems to Random Inputs Sysem: 5. Response of inear ime-invarian Sysems o Random Inpus 5.. Discree-ime linear ime-invarian (IV) sysems 5... Discree-ime IV sysem IV sysem xn ( ) yn ( ) [ xn ( )] Inpu Signal Sysem S Oupu Signal

More information

e 2t u(t) e 2t u(t) =?

e 2t u(t) e 2t u(t) =? EE : Signals, Sysems, and Transforms Fall 7. Skech he convoluion of he following wo signals. Tes No noes, closed book. f() Show your work. Simplify your answers. g(). Using he convoluion inegral, find

More information

Laplace Transforms. Examples. Is this equation differential? y 2 2y + 1 = 0, y 2 2y + 1 = 0, (y ) 2 2y + 1 = cos x,

Laplace Transforms. Examples. Is this equation differential? y 2 2y + 1 = 0, y 2 2y + 1 = 0, (y ) 2 2y + 1 = cos x, Laplace Transforms Definiion. An ordinary differenial equaion is an equaion ha conains one or several derivaives of an unknown funcion which we call y and which we wan o deermine from he equaion. The equaion

More information

EE 313 Linear Signals & Systems (Fall 2018) Solution Set for Homework #8 on Continuous-Time Signals & Systems

EE 313 Linear Signals & Systems (Fall 2018) Solution Set for Homework #8 on Continuous-Time Signals & Systems EE 33 Linear Signals & Sysems (Fall 08) Soluion Se for Homework #8 on Coninuous-Time Signals & Sysems By: Mr. Houshang Salimian & Prof. Brian L. Evans Here are several useful properies of he Dirac dela

More information

EECS20n, Solution to Midterm 2, 11/17/00

EECS20n, Solution to Midterm 2, 11/17/00 EECS20n, Soluion o Miderm 2, /7/00. 0 poins Wrie he following in Caresian coordinaes (i.e. in he form x + jy) (a) 2 poins j 3 j 2 + j += j ++j +=2 (b) 2 poins ( j)/( + j) = j (c) 2 poins cos π/4+jsin π/4

More information

Signal and System (Chapter 3. Continuous-Time Systems)

Signal and System (Chapter 3. Continuous-Time Systems) Signal and Sysem (Chaper 3. Coninuous-Time Sysems) Prof. Kwang-Chun Ho kwangho@hansung.ac.kr Tel: 0-760-453 Fax:0-760-4435 1 Dep. Elecronics and Informaion Eng. 1 Nodes, Branches, Loops A nework wih b

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se #2 Wha are Coninuous-Time Signals??? Reading Assignmen: Secion. of Kamen and Heck /22 Course Flow Diagram The arrows here show concepual flow beween ideas.

More information

System Processes input signal (excitation) and produces output signal (response)

System Processes input signal (excitation) and produces output signal (response) Signal A funcion of ime Sysem Processes inpu signal (exciaion) and produces oupu signal (response) Exciaion Inpu Sysem Oupu Response 1. Types of signals 2. Going from analog o digial world 3. An example

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signals & Sysems Prof. Mark Fowler Noe Se #1 C-T Sysems: Convoluion Represenaion Reading Assignmen: Secion 2.6 of Kamen and Heck 1/11 Course Flow Diagram The arrows here show concepual flow beween

More information

6.003 Homework #9 Solutions

6.003 Homework #9 Solutions 6.00 Homework #9 Soluions Problems. Fourier varieies a. Deermine he Fourier series coefficiens of he following signal, which is periodic in 0. x () 0 0 a 0 5 a k sin πk 5 sin πk 5 πk for k 0 a k 0 πk j

More information

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB EECS 6 Winer 7 Laboraory 3 Fourier series, Fourier ransform and Bode Plos in MATLAB Inroducion: The objecives of his lab are o use MATLAB:. To plo periodic signals wih Fourier series represenaion. To obain

More information

6.003 Homework #9 Solutions

6.003 Homework #9 Solutions 6.003 Homework #9 Soluions Problems. Fourier varieies a. Deermine he Fourier series coefficiens of he following signal, which is periodic in 0. x () 0 3 0 a 0 5 a k a k 0 πk j3 e 0 e j πk 0 jπk πk e 0

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Chapter 4 The Fourier Series and Fourier Transform

Chapter 4 The Fourier Series and Fourier Transform Represenaion of Signals in Terms of Frequency Componens Chaper 4 The Fourier Series and Fourier Transform Consider he CT signal defined by x () = Acos( ω + θ ), = The frequencies `presen in he signal are

More information

Notes 04 largely plagiarized by %khc

Notes 04 largely plagiarized by %khc Noes 04 largely plagiarized by %khc Convoluion Recap Some ricks: x() () =x() x() (, 0 )=x(, 0 ) R ț x() u() = x( )d x() () =ẋ() This hen ells us ha an inegraor has impulse response h() =u(), and ha a differeniaor

More information

ADDITIONAL PROBLEMS (a) Find the Fourier transform of the half-cosine pulse shown in Fig. 2.40(a). Additional Problems 91

ADDITIONAL PROBLEMS (a) Find the Fourier transform of the half-cosine pulse shown in Fig. 2.40(a). Additional Problems 91 ddiional Problems 9 n inverse relaionship exiss beween he ime-domain and freuency-domain descripions of a signal. Whenever an operaion is performed on he waveform of a signal in he ime domain, a corresponding

More information

Chapter One Fourier Series and Fourier Transform

Chapter One Fourier Series and Fourier Transform Chaper One I. Fourier Series Represenaion of Periodic Signals -Trigonomeric Fourier Series: The rigonomeric Fourier series represenaion of a periodic signal x() x( + T0 ) wih fundamenal period T0 is given

More information

8. Basic RL and RC Circuits

8. Basic RL and RC Circuits 8. Basic L and C Circuis This chaper deals wih he soluions of he responses of L and C circuis The analysis of C and L circuis leads o a linear differenial equaion This chaper covers he following opics

More information

( ) ( ) ( ) () () Signals And Systems Exam#1. 1. Given x(t) and y(t) below: x(t) y(t) (A) Give the expression of x(t) in terms of step functions.

( ) ( ) ( ) () () Signals And Systems Exam#1. 1. Given x(t) and y(t) below: x(t) y(t) (A) Give the expression of x(t) in terms of step functions. Signals And Sysems Exam#. Given x() and y() below: x() y() 4 4 (A) Give he expression of x() in erms of sep funcions. (%) x () = q() q( ) + q( 4) (B) Plo x(.5). (%) x() g() = x( ) h() = g(. 5) = x(. 5)

More information

6.003 Homework #8 Solutions

6.003 Homework #8 Solutions 6.003 Homework #8 Soluions Problems. Fourier Series Deermine he Fourier series coefficiens a k for x () shown below. x ()= x ( + 0) 0 a 0 = 0 a k = e /0 sin(/0) for k 0 a k = π x()e k d = 0 0 π e 0 k d

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Delhi Noida Bhopal Hyderabad Jaipur Lucknow Indore Pune Bhubaneswar Kolkata Patna Web: Ph:

Delhi Noida Bhopal Hyderabad Jaipur Lucknow Indore Pune Bhubaneswar Kolkata Patna Web:     Ph: Serial : 0. ND_NW_EE_Signal & Sysems_4068 Delhi Noida Bhopal Hyderabad Jaipur Lucknow Indore Pune Bhubaneswar Kolkaa Pana Web: E-mail: info@madeeasy.in Ph: 0-4546 CLASS TEST 08-9 ELECTRICAL ENGINEERING

More information

EECE.3620 Signal and System I

EECE.3620 Signal and System I EECE.360 Signal and Sysem I Hengyong Yu, PhD Associae Professor Deparmen of Elecrical and Compuer Engineering Universiy of Massachuses owell EECE.360 Signal and Sysem I Ch.9.4. Geomeric Evaluaion of he

More information

EE 301 Lab 2 Convolution

EE 301 Lab 2 Convolution EE 301 Lab 2 Convoluion 1 Inroducion In his lab we will gain some more experience wih he convoluion inegral and creae a scrip ha shows he graphical mehod of convoluion. 2 Wha you will learn This lab will

More information

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff Laplace ransfom: -ranslaion rule 8.03, Haynes Miller and Jeremy Orloff Inroducory example Consider he sysem ẋ + 3x = f(, where f is he inpu and x he response. We know is uni impulse response is 0 for

More information

Lecture 13 RC/RL Circuits, Time Dependent Op Amp Circuits

Lecture 13 RC/RL Circuits, Time Dependent Op Amp Circuits Lecure 13 RC/RL Circuis, Time Dependen Op Amp Circuis RL Circuis The seps involved in solving simple circuis conaining dc sources, resisances, and one energy-sorage elemen (inducance or capaciance) are:

More information

Laplace Transform and its Relation to Fourier Transform

Laplace Transform and its Relation to Fourier Transform Chaper 6 Laplace Transform and is Relaion o Fourier Transform (A Brief Summary) Gis of he Maer 2 Domains of Represenaion Represenaion of signals and sysems Time Domain Coninuous Discree Time Time () [n]

More information

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux Gues Lecures for Dr. MacFarlane s EE3350 Par Deux Michael Plane Mon., 08-30-2010 Wrie name in corner. Poin ou his is a review, so I will go faser. Remind hem o go lisen o online lecure abou geing an A

More information

The complex Fourier series has an important limiting form when the period approaches infinity, i.e., T 0. 0 since it is proportional to 1/L, but

The complex Fourier series has an important limiting form when the period approaches infinity, i.e., T 0. 0 since it is proportional to 1/L, but Fourier Transforms The complex Fourier series has an imporan limiing form when he period approaches infiniy, i.e., T or L. Suppose ha in his limi () k = nπ L remains large (ranging from o ) and (2) c n

More information

Signal processing. A. Sestieri Dipartimento di Meccanica e Aeronautica University La Sapienza, Rome

Signal processing. A. Sestieri Dipartimento di Meccanica e Aeronautica University La Sapienza, Rome Signal processing A. Sesieri Diparimeno di Meccanica e Aeronauica Universiy La Sapienza, Rome Presenaion layou - Fourier series and Fourier ransforms - Leakage - Aliasing - Analog versus digial signals

More information

Solutions of Sample Problems for Third In-Class Exam Math 246, Spring 2011, Professor David Levermore

Solutions of Sample Problems for Third In-Class Exam Math 246, Spring 2011, Professor David Levermore Soluions of Sample Problems for Third In-Class Exam Mah 6, Spring, Professor David Levermore Compue he Laplace ransform of f e from is definiion Soluion The definiion of he Laplace ransform gives L[f]s

More information

Block Diagram of a DCS in 411

Block Diagram of a DCS in 411 Informaion source Forma A/D From oher sources Pulse modu. Muliplex Bandpass modu. X M h: channel impulse response m i g i s i Digial inpu Digial oupu iming and synchronizaion Digial baseband/ bandpass

More information

f t te e = possesses a Laplace transform. Exercises for Module-III (Transform Calculus)

f t te e = possesses a Laplace transform. Exercises for Module-III (Transform Calculus) Exercises for Module-III (Transform Calculus) ) Discuss he piecewise coninuiy of he following funcions: =,, +, > c) e,, = d) sin,, = ) Show ha he funcion ( ) sin ( ) f e e = possesses a Laplace ransform.

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

Differential Equations

Differential Equations Mah 21 (Fall 29) Differenial Equaions Soluion #3 1. Find he paricular soluion of he following differenial equaion by variaion of parameer (a) y + y = csc (b) 2 y + y y = ln, > Soluion: (a) The corresponding

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier Represening a Signal Coninuous-ime ourier Mehods he convoluion mehod for finding he response of a sysem o an exciaion aes advanage of he lineariy and imeinvariance of he sysem and represens he exciaion

More information

Math 334 Fall 2011 Homework 11 Solutions

Math 334 Fall 2011 Homework 11 Solutions Dec. 2, 2 Mah 334 Fall 2 Homework Soluions Basic Problem. Transform he following iniial value problem ino an iniial value problem for a sysem: u + p()u + q() u g(), u() u, u () v. () Soluion. Le v u. Then

More information

(1) (2) Differentiation of (1) and then substitution of (3) leads to. Therefore, we will simply consider the second-order linear system given by (4)

(1) (2) Differentiation of (1) and then substitution of (3) leads to. Therefore, we will simply consider the second-order linear system given by (4) Phase Plane Analysis of Linear Sysems Adaped from Applied Nonlinear Conrol by Sloine and Li The general form of a linear second-order sysem is a c b d From and b bc d a Differeniaion of and hen subsiuion

More information

Solutions - Midterm Exam

Solutions - Midterm Exam DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, THE UNIVERITY OF NEW MEXICO ECE-34: ignals and ysems ummer 203 PROBLEM (5 PT) Given he following LTI sysem: oluions - Miderm Exam a) kech he impulse response

More information

Math Final Exam Solutions

Math Final Exam Solutions Mah 246 - Final Exam Soluions Friday, July h, 204 () Find explici soluions and give he inerval of definiion o he following iniial value problems (a) ( + 2 )y + 2y = e, y(0) = 0 Soluion: In normal form,

More information

δ (τ )dτ denotes the unit step function, and

δ (τ )dτ denotes the unit step function, and ECE-202 Homework Problems (Se 1) Spring 18 TO THE STUDENT: ALWAYS CHECK THE ERRATA on he web. ANCIENT ASIAN/AFRICAN/NATIVE AMERICAN/SOUTH AMERICAN ETC. PROVERB: If you give someone a fish, you give hem

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms 6- Chaper 6. Laplace Tranform 6.4 Shor Impule. Dirac Dela Funcion. Parial Fracion 6.5 Convoluion. Inegral Equaion 6.6 Differeniaion and Inegraion of Tranform 6.7 Syem of ODE 6.4 Shor Impule. Dirac Dela

More information

DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2010

DEPARTMENT 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 information

BEng (Hons) Telecommunications. Examinations for / Semester 2

BEng (Hons) Telecommunications. Examinations for / Semester 2 BEng (Hons) Telecommunicaions Cohor: BTEL/14/FT Examinaions for 2015-2016 / Semeser 2 MODULE: ELECTROMAGNETIC THEORY MODULE CODE: ASE2103 Duraion: 2 ½ Hours Insrucions o Candidaes: 1. Answer ALL 4 (FOUR)

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

Chapter 8 The Complete Response of RL and RC Circuits

Chapter 8 The Complete Response of RL and RC Circuits Chaper 8 The Complee Response of RL and RC Circuis Seoul Naional Universiy Deparmen of Elecrical and Compuer Engineering Wha is Firs Order Circuis? Circuis ha conain only one inducor or only one capacior

More information

ME 391 Mechanical Engineering Analysis

ME 391 Mechanical Engineering Analysis Fall 04 ME 39 Mechanical Engineering Analsis Eam # Soluions Direcions: Open noes (including course web posings). No books, compuers, or phones. An calculaor is fair game. Problem Deermine he posiion of

More information

Complete solutions to Exercise 14(b) 1. Very similar to EXAMPLE 4. We have same characteristic equation:

Complete solutions to Exercise 14(b) 1. Very similar to EXAMPLE 4. We have same characteristic equation: Soluions 4(b) Complee soluions o Exercise 4(b). Very similar o EXAMPE 4. We have same characerisic equaion: 5 i Ae = + Be By using he given iniial condiions we obain he simulaneous equaions A+ B= 0 5A

More information

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems Sample Final Exam Covering Chaper 9 (final04) Sample Final Exam (final03) Covering Chaper 9 of Fundamenal of Signal & Syem Problem (0 mar) Conider he caual opamp circui iniially a re depiced below. I LI

More information

III-A. Fourier Series Expansion

III-A. Fourier Series Expansion Summer 28 Signals & Sysems S.F. Hsieh III-A. Fourier Series Expansion Inroducion. Divide and conquer Signals can be decomposed as linear combinaions of: (a) shifed impulses: (sifing propery) Why? x() x()δ(

More information

Chapter 2 : Fourier Series. Chapter 3 : Fourier Series

Chapter 2 : Fourier Series. Chapter 3 : Fourier Series Chaper 2 : Fourier Series.0 Inroducion Fourier Series : represenaion of periodic signals as weighed sums of harmonically relaed frequencies. If a signal x() is periodic signal, hen x() can be represened

More information

Traveling Waves. Chapter Introduction

Traveling Waves. Chapter Introduction Chaper 4 Traveling Waves 4.1 Inroducion To dae, we have considered oscillaions, i.e., periodic, ofen harmonic, variaions of a physical characerisic of a sysem. The sysem a one ime is indisinguishable from

More information

Solution of Integro-Differential Equations by Using ELzaki Transform

Solution of Integro-Differential Equations by Using ELzaki Transform Global Journal of Mahemaical Sciences: Theory and Pracical. Volume, Number (), pp. - Inernaional Research Publicaion House hp://www.irphouse.com Soluion of Inegro-Differenial Equaions by Using ELzaki Transform

More information

EELE Lecture 8 Example of Fourier Series for a Triangle from the Fourier Transform. Homework password is: 14445

EELE Lecture 8 Example of Fourier Series for a Triangle from the Fourier Transform. Homework password is: 14445 EELE445-4 Lecure 8 Eample o Fourier Series or a riangle rom he Fourier ransorm Homework password is: 4445 3 4 EELE445-4 Lecure 8 LI Sysems and Filers 5 LI Sysem 6 3 Linear ime-invarian Sysem Deiniion o

More information

Chapter 7 Response of First-order RL and RC Circuits

Chapter 7 Response of First-order RL and RC Circuits Chaper 7 Response of Firs-order RL and RC Circuis 7.- The Naural Response of RL and RC Circuis 7.3 The Sep Response of RL and RC Circuis 7.4 A General Soluion for Sep and Naural Responses 7.5 Sequenial

More information

Continuous Time Linear Time Invariant (LTI) Systems. Dr. Ali Hussein Muqaibel. Introduction

Continuous Time Linear Time Invariant (LTI) Systems. Dr. Ali Hussein Muqaibel. Introduction /9/ Coninuous Time Linear Time Invarian (LTI) Sysems Why LTI? Inroducion Many physical sysems. Easy o solve mahemaically Available informaion abou analysis and design. We can apply superposiion LTI Sysem

More information

System of Linear Differential Equations

System of Linear Differential Equations Sysem of Linear Differenial Equaions In "Ordinary Differenial Equaions" we've learned how o solve a differenial equaion for a variable, such as: y'k5$e K2$x =0 solve DE yx = K 5 2 ek2 x C_C1 2$y''C7$y

More information

Lecture 1 Overview. course mechanics. outline & topics. what is a linear dynamical system? why study linear systems? some examples

Lecture 1 Overview. course mechanics. outline & topics. what is a linear dynamical system? why study linear systems? some examples EE263 Auumn 27-8 Sephen Boyd Lecure 1 Overview course mechanics ouline & opics wha is a linear dynamical sysem? why sudy linear sysems? some examples 1 1 Course mechanics all class info, lecures, homeworks,

More information

Chapter 3: Signal Transmission and Filtering. A. Bruce Carlson Paul B. Crilly 2010 The McGraw-Hill Companies

Chapter 3: Signal Transmission and Filtering. A. Bruce Carlson Paul B. Crilly 2010 The McGraw-Hill Companies Communicaion Sysems, 5e Chaper 3: Signal Transmission and Filering A. Bruce Carlson Paul B. Crilly 00 The McGraw-Hill Companies Chaper 3: Signal Transmission and Filering Response of LTI sysems Signal

More information

Homework 6 AERE331 Spring 2019 Due 4/24(W) Name Sec. 1 / 2

Homework 6 AERE331 Spring 2019 Due 4/24(W) Name Sec. 1 / 2 Homework 6 AERE33 Spring 9 Due 4/4(W) Name Sec / PROBLEM (5p In PROBLEM 4 of HW4 we used he frequency domain o design a yaw/rudder feedback conrol sysem for a plan wih ransfer funcion 46 Gp () s The conroller

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

6.302 Feedback Systems Recitation 4: Complex Variables and the s-plane Prof. Joel L. Dawson

6.302 Feedback Systems Recitation 4: Complex Variables and the s-plane Prof. Joel L. Dawson Number 1 quesion: Why deal wih imaginary and complex numbers a all? One answer is ha, as an analyical echnique, hey make our lives easier. Consider passing a cosine hrough an LTI filer wih impulse response

More information

B Signals and Systems I Solutions to Midterm Test 2. xt ()

B Signals and Systems I Solutions to Midterm Test 2. xt () 34-33B Signals and Sysems I Soluions o Miderm es 34-33B Signals and Sysems I Soluions o Miderm es ednesday Marh 7, 7:PM-9:PM Examiner: Prof. Benoi Boule Deparmen of Elerial and Compuer Engineering MGill

More information

2 int T. is the Fourier transform of f(t) which is the inverse Fourier transform of f. i t e

2 int T. is the Fourier transform of f(t) which is the inverse Fourier transform of f. i t e PHYS67 Class 3 ourier Transforms In he limi T, he ourier series becomes an inegral ( nt f in T ce f n f f e d, has been replaced by ) where i f e d is he ourier ransform of f() which is he inverse ourier

More information

RC, RL and RLC circuits

RC, RL and RLC circuits Name Dae Time o Complee h m Parner Course/ Secion / Grade RC, RL and RLC circuis Inroducion In his experimen we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors.

More information

ES 250 Practice Final Exam

ES 250 Practice Final Exam ES 50 Pracice Final Exam. Given ha v 8 V, a Deermine he values of v o : 0 Ω, v o. V 0 Firs, v o 8. V 0 + 0 Nex, 8 40 40 0 40 0 400 400 ib i 0 40 + 40 + 40 40 40 + + ( ) 480 + 5 + 40 + 8 400 400( 0) 000

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms Chaper 6. Laplace Tranform Kreyzig by YHLee;45; 6- An ODE i reduced o an algebraic problem by operaional calculu. The equaion i olved by algebraic manipulaion. The reul i ranformed back for he oluion of

More information

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

h[n] is the impulse response of the discrete-time system:

h[n] is the impulse response of the discrete-time system: Definiion Examples Properies Memory Inveribiliy Causaliy Sabiliy Time Invariance Lineariy Sysems Fundamenals Overview Definiion of a Sysem x() h() y() x[n] h[n] Sysem: a process in which inpu signals are

More information

ME 452 Fourier Series and Fourier Transform

ME 452 Fourier Series and Fourier Transform ME 452 Fourier Series and Fourier ransform Fourier series From Joseph Fourier in 87 as a resul of his sudy on he flow of hea. If f() is almos any periodic funcion i can be wrien as an infinie sum of sines

More information

6.2 Transforms of Derivatives and Integrals.

6.2 Transforms of Derivatives and Integrals. SEC. 6.2 Transforms of Derivaives and Inegrals. ODEs 2 3 33 39 23. Change of scale. If l( f ()) F(s) and c is any 33 45 APPLICATION OF s-shifting posiive consan, show ha l( f (c)) F(s>c)>c (Hin: In Probs.

More information

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations IOSR Journal of Mahemaics (IOSR-JM) e-issn: 2278-5728, p-issn: 2319-765X. Volume 1, Issue 6 Ver. II (Nov - Dec. 214), PP 48-54 Variaional Ieraion Mehod for Solving Sysem of Fracional Order Ordinary Differenial

More information

6.003 Homework #13 Solutions

6.003 Homework #13 Solutions 6.003 Homework #3 Soluions Problems. Transformaion Consider he following ransformaion from x() o y(): x() w () w () w 3 () + y() p() cos() where p() = δ( k). Deermine an expression for y() when x() = sin(/)/().

More information

Lecture 2: Optics / C2: Quantum Information and Laser Science

Lecture 2: Optics / C2: Quantum Information and Laser Science Lecure : Opics / C: Quanum Informaion and Laser Science Ocober 9, 8 1 Fourier analysis This branch of analysis is exremely useful in dealing wih linear sysems (e.g. Maxwell s equaions for he mos par),

More information

INDEX. Transient analysis 1 Initial Conditions 1

INDEX. Transient analysis 1 Initial Conditions 1 INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera

More information

18.03SC Unit 3 Practice Exam and Solutions

18.03SC Unit 3 Practice Exam and Solutions Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care

More information

Signals and Systems Linear Time-Invariant (LTI) Systems

Signals and Systems Linear Time-Invariant (LTI) Systems Signals and Sysems Linear Time-Invarian (LTI) Sysems Chang-Su Kim Discree-Time LTI Sysems Represening Signals in Terms of Impulses Sifing propery 0 x[ n] x[ k] [ n k] k x[ 2] [ n 2] x[ 1] [ n1] x[0] [

More information

Signals and Systems Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin

Signals and Systems Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin EE 345S Real-Time Digial Signal Processing Lab Spring 26 Signals and Sysems Prof. Brian L. Evans Dep. of Elecrical and Compuer Engineering The Universiy of Texas a Ausin Review Signals As Funcions of Time

More information

EE102 Homework 5 and 6 Solutions

EE102 Homework 5 and 6 Solutions EE2 Prof. S. Boyd EE2 Homework 5 and 6 Soluions 35. The verical dynamics of a vehicle suspension sysem, when he vehicle is driving on level ground, are given by (m v + m l )d () + bd () + kd() =. Here

More information

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t M ah 5 2 7 Fall 2 0 0 9 L ecure 1 0 O c. 7, 2 0 0 9 Hamilon- J acobi Equaion: Explici Formulas In his lecure we ry o apply he mehod of characerisics o he Hamilon-Jacobi equaion: u + H D u, x = 0 in R n

More information

Lectures 29 and 30 BIQUADRATICS AND STATE SPACE OP AMP REALIZATIONS. I. Introduction

Lectures 29 and 30 BIQUADRATICS AND STATE SPACE OP AMP REALIZATIONS. I. Introduction EE-202/445, 3/18/18 9-1 R. A. DeCarlo Lecures 29 and 30 BIQUADRATICS AND STATE SPACE OP AMP REALIZATIONS I. Inroducion 1. The biquadraic ransfer funcion has boh a 2nd order numeraor and a 2nd order denominaor:

More information

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions MA 14 Calculus IV (Spring 016) Secion Homework Assignmen 1 Soluions 1 Boyce and DiPrima, p 40, Problem 10 (c) Soluion: In sandard form he given firs-order linear ODE is: An inegraing facor is given by

More information

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow KEY Mah 334 Miderm III Winer 008 secion 00 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

Problemas das Aulas Práticas

Problemas das Aulas Práticas Mesrado Inegrado em Engenharia Elecroécnica e de Compuadores Conrolo em Espaço de Esados Problemas das Aulas Práicas J. Miranda Lemos Fevereiro de 3 Translaed o English by José Gaspar, 6 J. M. Lemos, IST

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

Outline Chapter 2: Signals and Systems

Outline Chapter 2: Signals and Systems Ouline Chaper 2: Signals and Sysems Signals Basics abou Signal Descripion Fourier Transform Harmonic Decomposiion of Periodic Waveforms (Fourier Analysis) Definiion and Properies of Fourier Transform Imporan

More information

6.003: Signal Processing

6.003: Signal Processing 6.003: Signal Processing Coninuous-Time Fourier Transform Definiion Examples Properies Relaion o Fourier Series Sepember 5, 08 Quiz Thursday, Ocober 4, from 3pm o 5pm. No lecure on Ocober 4. The exam is

More information

Time Domain Transfer Function of the Induction Motor

Time Domain Transfer Function of the Induction Motor Sudies in Engineering and Technology Vol., No. ; Augus 0 ISSN 008 EISSN 006 Published by Redfame Publishing URL: hp://se.redfame.com Time Domain Transfer Funcion of he Inducion Moor N N arsoum Correspondence:

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information