12. Nyquist Sampling, Pulse-Amplitude Modulation, and Time- Division Multiplexing
|
|
- Ashlynn Rice
- 6 years ago
- Views:
Transcription
1 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac 2. Nyqui Sapling, Pule-Apliude Modulaion, and Tie- Diviion Muliplexing Many analogue counicaion ye are ill in wide ue oday. Thee include AM, FM, and PM ye. I analogue ignal are o be ranied digially, hey have o be convered o dicree aple. The converion o an analogue ignal ino a dicree-ie apled ignal i accoplihed by apling he analogue ignal a regular ie inerval T. T i called he apling period and = / T i known a he apling rae. Deiniion []. A ignal ( i called a band-liied ignal i M( = or > Hz (2. where i he highe-requency pecral coponen o (. Conider a periodic recangular waveor ( o period T = /, uni apliude, and pule widh. The rigonoeric Fourier erie o ( i ( = T + 2 ( in 2πn /2 T n = 2πn /2 co 2πn (2.2 c = T + 2 c T n co 2πn (2.3 n = = d + 2d n = in co 2πn (2.4 where c =, c n = Fourier erie i in, and d = T. The correponding exponenial ( = d n = in e j 2πn (2.5 I we uliply ( by (, we obain c ( = ( ( = ( (d + 2d n = = d( ( + 2 n = in in co 2πn co 2πn (2.6 c ( coni o he coponen ( and an ininie nuber o DSB ignal a 2.
2 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac apling requencie, 2, 3, The Fourier ranor o c ( i S c ( = dm( + d n = in [M( - n + M( + n ] (2.7 Figure 2. how he waveor and pecra aociaed wih ignal apling. Figure 2. Waveor and pecra aociaed wih ignal apling. Figure 2.2 how wha happen i = 2 and < 2. Figure 2.2 Signal pecra or (a = 2 and (b < 2. Since he bandwidh o ( i, we ee ha he pecra do no overlap i > 2 and he pecru aociaed wih he ignal ( can be eparaed ro oher uing a low-pa iler wih a cuo requency o. When < 2, he pecra overlap. Since he requency conen in hee region o overlap add, he ignal i diored. The diorion i called aliaing and i i no longer poible o recover ( ro i aple value by low-pa ilering. Sapling Theore [2] Le (nt be he aple value o ( where n i an ineger. The apling heore ae ha he ignal ( can be reconruced ro (nt wih no diorion i he apling requency > 2. The iniu apling rae 2 i called he Nyqui apling rae. Proo. Since M( i a non-periodic bandliied uncion, we can ake a new uncion which i periodic a requency bu no overlapping in he requency-doain. Le he periodic requency uncion be Mp (, a hown in Figure 2.3. M( i a band-liied verion o M p (, Figure 2.3 M( repreened a a periodic requency uncion. The exponenial Fourier erie o M p ( i M p ( = c n e jn (2.8 n = where > 2 and 2.2
3 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac = 2π/ (2.9 The coeicien c n are given by c n = /2 M p (e -jn d = /2 /2 M p ( e -jn(2π/ d (2. /2 However, he Fourier ranor ell u ha ( = F - [M(] = M( e j2π d = /2 M p ( e j2π d /2 (2. Coparing equaion (2. and (2., we ee ha, i = n, we obain c n = ( n (2.2 Thi ay ha we can obain each c n ro he aple value o ( a ie = n. Once c n i known, we can obain M p ( ro equaion (2.8, and once M p ( i known, we can obain ( ro equaion (2.. Subiuing c n ino equaion (2.8, we ge M p ( = n = ( n e jn (2.3 Subiuing hi expreion or M p ( ino equaion (2., we ge /2 ( = F - [M(] = [ ( n /2 n = e jn ] e j2π d /2 = n = ( n e jn e j2π d /2 = n = ( n in[ π ( n ] π ( n 2.3
4 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac = n = ( n in [π ( n ] π ( n Weighing acor (2.4 Equaion (2.4 how ha each aple i uliplied by a weighing acor. Signal Reconrucion [2, 3] The proce o reconrucing an analogue ignal ( ro i aple i known a inerpolaion. How do we reconruc ( ro i aple ( n? Conider he aple ignal o ( hown in Figure 2.4. Figure 2.4 Saple o (. Le M n ( be he Fourier ranor o he n-h aple ( n. I << /, ( can be aued o be conan over he apling ie and /2 M n ( = ( n e -j2π d ( n /2 e -j2π(n/ /2 d /2 M n ( ( n e -j2π(n/ (2.5 Fro our knowledge o baic PAM heory, we can recover he analogue ignal uing a low-pa iler wih a cuo requency o /2 (>. Aue ha we have an ideal low-pa iler whoe raner uncion i H( = K e -j2π d, where K i a conan and d i a ie delay. Wihou lo o generaliy, we e he iler gain K = and he iler delay d =. Le g n ( be he iler oupu repone o he n-h inpu aple ( n. The Fourier ranor o g n ( i G n ( = H(M n ( = M n ( and 2.4
5 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac g n ( /2 = G n ( e j2π d = G n ( e j2π d /2 = ( n in[ π ( n ] π ( n (2.6 For a linear ideal iler, he iler oupu repone o all inpu aple i ju he u o he iler oupu o each inpu aple, or g( = g n ( n = = n = ( n in[ π ( n ] π ( n (2.7 = ( (2.8 Equaion (2.7 yield value o g( beween aple a a weighed u o all aple value. g( i no only deined a he apling inan, bu i i proporional o ( a all inan o ie. Thi i hown in Figure 2.5. Figure 2.5 Filer repone o inpu aple. Pracical Sapling Frequency and Pule-Apliude Modulaion Table 2. Pracical apling requency value or audio and broadca ignal Signal > 2 Acual apling requency Audio 3.3 khz > 6.6 khz 8 khz Muic 2 khz > 4 khz 44. khz TV 4 MHz > 8 MHz The apling heore i very iporan becaue i allow u o replace an analogue ignal by a dicree aple and reconruc he analogue ignal ro i aple value. I open door o any new echnique o counicaing analogue ignal by aple. A ye raniing aple value o he analogue ignal i called a pule-apliude odulaion (PAM ye and i hown in Figure 2.6. Figure 2.6 PAM ye. 2.5
6 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac Tie Diviion Muliplexing (TDM One o he baic proble in counicaion engineering i he deign o a pule counicaion ye which allow ignal ro any uer o be ranied iulaneouly over a ingle counicaion channel. We ee ro he apling proce ha, wih << T, here i a ie gap beween wo conecuive aple in a ingle-uer PAM ye. Suppoe ha we have everal dieren ignal o he ae or dieren bandwidh. I we aple he ignal in a equenial anner, we can pu he aple in he ie gap. All hee ignal aple can now be ranied along a ingle counicaion channel. A he receiving end, he ignal can be eparaed and recovered. We now have a ie-uliplexed ye. Such a uliplexing echnique i called ie diviion uliplexing (TDM. I peri he iulaneou raniion o everal ignal on a ie-hared bai. Figure 2.7 how he ranier, he receiver, and he pecru o a 5-uer TDM PAM ye wih = 8 aple/. Figure 2.7 TDM ye. Reerence [] H. P. Hu, analog and Digial Counicaion, McGraw-Hill, 993. [2] M. Schwarz, Inoraion Traniion, Modulaion, and Noie, 4/e, McGraw-Hill, 99. [3] M. S. Roden, Analog and Digial Counicaion Sye, 3/e, Prenice Hall,
7 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac ( M ( ( -T T 2 2 ( c Envelope Envelope c n T - 2 T M( S ( c 2 T Guard band Figure 2. Waveor and pecra aociaed wih ignal apling. 2.7
8 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac Envelope S c ( T M( - (a 2 =2 Envelope S ( c T M( - 2 Region o overlap < 2 (b Figure 2.2 Signal pecra or (a = 2 and (b < 2. M ( p M ( Figure 2.3 M( ued o ake a periodic requency uncion. 2.8
9 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac ( ( Saple o ( T <<T Figure 2.4 Saple o (. g g n ( n ( ( ( Reconruced ignal g n +( ( n -2 n - n n + n +2 Figure 2.5 Filer repone o inpu ignal aple. ( c ( Sapler PAM ignal Tranier // LPF ~ ~ Recovered ignal Receiver Figure 2.6 PAM ye. 2.9
10 Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac ( ( 2 ( 5 = 8 aple/ c ( Copoie PAM ignal // LPF ~ ~ ~ ~ ~ ~ ^ ( ^ ( 2 ^ ( 5 Source Deinaion (a Tranier and receiver c ( 25 µ 25 µ (b Waveor o TDM ignal Figure 2.7 TDM ye. 2.
Interpolation and Pulse Shaping
EE345S Real-Time Digial Signal Proceing Lab Spring 2006 Inerpolaion and Pule Shaping Prof. Brian L. Evan Dep. of Elecrical and Compuer Engineering The Univeriy of Texa a Auin Lecure 7 Dicree-o-Coninuou
More informationNotes on MRI, Part II
BME 483 MRI Noe : page 1 Noe on MRI, Par II Signal Recepion in MRI The ignal ha we deec in MRI i a volage induced in an RF coil by change in agneic flu fro he preceing agneizaion in he objec. One epreion
More informationProblem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.
CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex
More information6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson
6.32 Feedback Syem Phae-locked loop are a foundaional building block for analog circui deign, paricularly for communicaion circui. They provide a good example yem for hi cla becaue hey are an excellen
More information8.1. a) For step response, M input is u ( t) Taking inverse Laplace transform. as α 0. Ideal response, K c. = Kc Mτ D + For ramp response, 8-1
8. a For ep repone, inpu i u, U Y a U α α Y a α α Taking invere Laplae ranform a α e e / α / α A α 0 a δ 0 e / α a δ deal repone, α d Y i Gi U i δ Hene a α 0 a i For ramp repone, inpu i u, U Soluion anual
More information5.5 Sampling. The Connection Between: Continuous Time & Discrete Time
5.5 Sampling he Connection Between: Continuou ime & Dicrete ime Warning: I don t really like how the book cover thi! It i not that it i wrong it jut ail to make the correct connection between the mathematic
More informationExponential Sawtooth
ECPE 36 HOMEWORK 3: PROPERTIES OF THE FOURIER TRANSFORM SOLUTION. Exponenial Sawooh: The eaie way o do hi problem i o look a he Fourier ranform of a ingle exponenial funcion, () = exp( )u(). From he able
More informationApplication of Combined Fourier Series Transform (Sampling Theorem)
Applicaion o Combined Fourier Serie ranorm Sampling heorem x X[] m m Sampling Frequency Deparmen o Elecrical and Compuer Engineering Deparmen o Elecrical and Compuer Engineering X[] x We need Fourier Serie
More informationDirect Sequence Spread Spectrum II
DS-SS II 7. Dire Sequene Spread Speru II ER One igh hink ha DS-SS would have he following drawak. Sine he RF andwidh i ie ha needed for a narrowand PSK ignal a he ae daa rae R, here will e ie a uh noie
More informationCHAPTER 7: SECOND-ORDER CIRCUITS
EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha
More informationTutorial Sheet #2 discrete vs. continuous functions, periodicity, sampling
2.39 Tuorial Shee #2 discree vs. coninuous uncions, periodiciy, sampling We will encouner wo classes o signals in his class, coninuous-signals and discree-signals. The disinc mahemaical properies o each,
More informationPhysics 240: Worksheet 16 Name
Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,
More informationCONTROL SYSTEMS. Chapter 10 : State Space Response
CONTROL SYSTEMS Chaper : Sae Space Repone GATE Objecive & Numerical Type Soluion Queion 5 [GATE EE 99 IIT-Bombay : Mark] Conider a econd order yem whoe ae pace repreenaion i of he form A Bu. If () (),
More informationSample 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 informationLinear Motion, Speed & Velocity
Add Iporan Linear Moion, Speed & Velociy Page: 136 Linear Moion, Speed & Velociy NGSS Sandard: N/A MA Curriculu Fraework (2006): 1.1, 1.2 AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3 Knowledge/Underanding
More informationUNIVERSITY OF TRENTO MEASUREMENTS OF TRANSIENT PHENOMENA WITH DIGITAL OSCILLOSCOPES. Antonio Moschitta, Fabrizio Stefani, Dario Petri.
UNIVERSIY OF RENO DEPARMEN OF INFORMAION AND COMMUNICAION ECHNOLOGY 385 Povo reno Ialy Via Sommarive 4 hp://www.di.unin.i MEASUREMENS OF RANSIEN PHENOMENA WIH DIGIAL OSCILLOSCOPES Anonio Moschia Fabrizio
More informationLet. x y. denote a bivariate time series with zero mean.
Linear Filer Le x y : T denoe a bivariae ime erie wih zero mean. Suppoe ha he ime erie {y : T} i conruced a follow: y a x The ime erie {y : T} i aid o be conruced from {x : T} by mean of a Linear Filer.
More informationEE Control Systems LECTURE 2
Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian
More informationMobile Communications TCS 455
Mobile Counication TCS 455 Dr. Prapun Sukopong prapun@iit.tu.ac.th Lecture 24 1 Office Hour: BKD 3601-7 Tueday 14:00-16:00 Thurday 9:30-11:30 Announceent Read Chapter 9: 9.1 9.5 Section 1.2 fro [Bahai,
More information, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max
ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen
More informationLecture 4. Goals: Be able to determine bandwidth of digital signals. Be able to convert a signal from baseband to passband and back IV-1
Lecure 4 Goals: Be able o deermine bandwidh o digial signals Be able o conver a signal rom baseband o passband and back IV-1 Bandwidh o Digial Daa Signals A digial daa signal is modeled as a random process
More informationChapter 2: Problem Solutions
Chapter 2: Solution Dicrete Time Proceing of Continuou Time Signal Sampling à 2.. : Conider a inuoidal ignal and let u ample it at a frequency F 2kHz. xt 3co000t 0. a) Determine and expreion for the ampled
More informationFrequency Response. We now know how to analyze and design ccts via s- domain methods which yield dynamical information
Frequency Repone We now now how o analyze and deign cc via - domain mehod which yield dynamical informaion Zero-ae repone Zero-inpu repone Naural repone Forced repone The repone are decribed by he exponenial
More informationCSE/NEUBEH 528 Modeling Synapses and Networks (Chapter 7)
CSE/NEUBEH 528 Modeling Synape and Nework (Chaper 7) Iage fro Wikiedia Coon 1 Lecure figure are fro Dayan & Ao ook Coure Suary (hu far) F Neural Encoding Wha ake a neuron fire? (STA, covariance analyi)
More information28. Narrowband Noise Representation
Narrowband Noise Represenaion on Mac 8. Narrowband Noise Represenaion In mos communicaion sysems, we are ofen dealing wih band-pass filering of signals. Wideband noise will be shaped ino bandlimied noise.
More informationTo become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship
Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,
More informationEnergy Problems 9/3/2009. W F d mgh m s 196J 200J. Understanding. Understanding. Understanding. W F d. sin 30
9/3/009 nderanding Energy Proble Copare he work done on an objec o a.0 kg a) In liing an objec 0.0 b) Puhing i up a rap inclined a 30 0 o he ae inal heigh 30 0 puhing 0.0 liing nderanding Copare he work
More informationMore on ODEs by Laplace Transforms October 30, 2017
More on OE b Laplace Tranfor Ocober, 7 More on Ordinar ifferenial Equaion wih Laplace Tranfor Larr areo Mechanical Engineering 5 Seinar in Engineering nali Ocober, 7 Ouline Review la cla efiniion of Laplace
More informationHow to Solve System Dynamic s Problems
How o Solve Sye Dynaic Proble A ye dynaic proble involve wo or ore bodie (objec) under he influence of everal exernal force. The objec ay uliaely re, ove wih conan velociy, conan acceleraion or oe cobinaion
More informationAlgorithmic Discrete Mathematics 6. Exercise Sheet
Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap
More informationFourier Series & The Fourier Transform. Joseph Fourier, our hero. Lord Kelvin on Fourier s theorem. What do we want from the Fourier Transform?
ourier Series & The ourier Transfor Wha is he ourier Transfor? Wha do we wan fro he ourier Transfor? We desire a easure of he frequencies presen in a wave. This will lead o a definiion of he er, he specru.
More informationDiscussion Session 2 Constant Acceleration/Relative Motion Week 03
PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll
More informationu(t) Figure 1. Open loop control system
Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference
More informationDesign of Digital Filters
Deign of Digital Filter Paley-Wiener Theorem [ ] ( ) If h n i a caual energy ignal, then ln H e dω< B where B i a finite upper bound. One implication of the Paley-Wiener theorem i that a tranfer function
More informationEELE 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 informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual
More informationLecture #6: Continuous-Time Signals
EEL5: Discree-Time Signals and Sysems Lecure #6: Coninuous-Time Signals Lecure #6: Coninuous-Time Signals. Inroducion In his lecure, we discussed he ollowing opics:. Mahemaical represenaion and ransormaions
More informationChapter 9 Sinusoidal Steady State Analysis
Chaper 9 Sinusoidal Seady Sae Analysis 9.-9. The Sinusoidal Source and Response 9.3 The Phasor 9.4 pedances of Passive Eleens 9.5-9.9 Circui Analysis Techniques in he Frequency Doain 9.0-9. The Transforer
More informationChapter 7: Inverse-Response Systems
Chaper 7: Invere-Repone Syem Normal Syem Invere-Repone Syem Baic Sar ou in he wrong direcion End up in he original eady-ae gain value Two or more yem wih differen magniude and cale in parallel Main yem
More informatione 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 informationIntroduction to Congestion Games
Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game
More informationDEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING EXAMINATIONS 2008
[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
More information18.03SC 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 informationCommunication Systems, 5e
Communicaion Sysems, 5e Chaper : Signals and Specra A. Bruce Carlson Paul B. Crilly The McGraw-Hill Companies Chaper : Signals and Specra Line specra and ourier series Fourier ransorms Time and requency
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 30 Signal & Syem Prof. ark Fowler oe Se #34 C-T Tranfer Funcion and Frequency Repone /4 Finding he Tranfer Funcion from Differenial Eq. Recall: we found a DT yem Tranfer Funcion Hz y aking he ZT of
More informationSOLUTIONS 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 informationRandomized Perfect Bipartite Matching
Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for
More informationSignals 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 information13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13.
Chaper 3 The Laplace Tranform in Circui Analyi 3. Circui Elemen in he Domain 3.-3 Circui Analyi in he Domain 3.4-5 The Tranfer Funcion and Naural Repone 3.6 The Tranfer Funcion and he Convoluion Inegral
More informationinto a discrete time function. Recall that the table of Laplace/z-transforms is constructed by (i) selecting to get
Lecture 25 Introduction to Some Matlab c2d Code in Relation to Sampled Sytem here are many way to convert a continuou time function, { h( t) ; t [0, )} into a dicrete time function { h ( k) ; k {0,,, }}
More informationEE 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 informationChapter 7: Solving Trig Equations
Haberman MTH Secion I: The Trigonomeric Funcions Chaper 7: Solving Trig Equaions Le s sar by solving a couple of equaions ha involve he sine funcion EXAMPLE a: Solve he equaion sin( ) The inverse funcions
More informationRoadmap for Discrete-Time Signal Processing
EE 4G Note: Chapter 8 Continuou-time Signal co(πf Roadmap for Dicrete-ime Signal Proceing.5 -.5 -..4.6.8..4.6.8 Dicrete-time Signal (Section 8.).5 -.5 -..4.6.8..4.6.8 Sampling Period econd (or ampling
More informationChapter 2. Sampling. 2.1 Sampling. Impulse Sampling 2-1
2- Chaper 2 Sampling 2. Sampling In his chaper, we sudy he represenaion o a coninuous-ime signal by is samples. his is provided in erms o he sampling heorem. Consider hree coninuous-ime signals x (), x
More informationEECE 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 informationSingle Phase Line Frequency Uncontrolled Rectifiers
Single Phae Line Frequency Unconrolle Recifier Kevin Gaughan 24-Nov-03 Single Phae Unconrolle Recifier 1 Topic Baic operaion an Waveform (nucive Loa) Power Facor Calculaion Supply curren Harmonic an Th
More informationConsider a Binary antipodal system which produces data of δ (t)
Modulaion Polem PSK: (inay Phae-hi keying) Conide a inay anipodal yem whih podue daa o δ ( o + δ ( o inay and epeively. Thi daa i paed o pule haping ile and he oupu o he pule haping ile i muliplied y o(
More information#5 Demodulation and Detection Error due to Noise
06 Q Wirele Communicaion Engineering #5 Demodulaion and Deecion Error due o Noie Kei Sakaguci akaguci@mobile.ee. Jul 8, 06 Coure Scedule Dae Tex Conen # June 7, 7 Inroducion o wirele communicaion em #
More informationChapter 2 Sampling and Quantization. In order to investigate sampling and quantization, the difference between analog
Chapter Sampling and Quantization.1 Analog and Digital Signal In order to invetigate ampling and quantization, the difference between analog and digital ignal mut be undertood. Analog ignal conit of continuou
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Civil and Environmental Engineering
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Deparmen of Civil and Environmenal Engineering 1.731 Waer Reource Syem Lecure 17 River Bain Planning Screening Model Nov. 7 2006 River Bain Planning River bain planning
More informationPHYSICS 151 Notes for Online Lecture #4
PHYSICS 5 Noe for Online Lecure #4 Acceleraion The ga pedal in a car i alo called an acceleraor becaue preing i allow you o change your elociy. Acceleraion i how fa he elociy change. So if you ar fro re
More information6.003 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 informationLinear Response Theory: The connection between QFT and experiments
Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and
More informationEE202 Circuit Theory II
EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C
More informationDelhi 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 informationLecture #7. EECS490: Digital Image Processing. Image Processing Example Fuzzy logic. Fourier Transform. Basics Image processing examples
Lecure #7 Image Processing Example Fuzzy logic Basics Image processing examples Fourier Transorm Inner produc, basis uncions Fourier series Image Processing Example original image Laplacian o image (c)
More informationBlock 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 informationDesign of Controller for Robot Position Control
eign of Conroller for Robo oiion Conrol Two imporan goal of conrol: 1. Reference inpu racking: The oupu mu follow he reference inpu rajecory a quickly a poible. Se-poin racking: Tracking when he reference
More informationChapter 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 informationNotes 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 informationElastic and Inelastic Collisions
laic and Inelaic Colliion In an LASTIC colliion, energy i conered (Kbefore = Kafer or Ki = Kf. In an INLASTIC colliion, energy i NOT conered. (Ki > Kf. aple: A kg block which i liding a 0 / acro a fricionle
More informationAdmin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t)
/0/ dmin lunch oday rading MX LOW PPLIION 0, pring avid Kauchak low graph/nework low nework direced, weighed graph (V, ) poiive edge weigh indicaing he capaciy (generally, aume ineger) conain a ingle ource
More informationRectilinear Kinematics
Recilinear Kinemaic Coninuou Moion Sir Iaac Newon Leonard Euler Oeriew Kinemaic Coninuou Moion Erraic Moion Michael Schumacher. 7-ime Formula 1 World Champion Kinemaic The objecie of kinemaic i o characerize
More information6.8 Laplace Transform: General Formulas
48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy
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
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 informationCHAPTER 3 SIGNALS & SYSTEMS. z -transform in the z -plane will be (A) 1 (B) 1 (D) (C) . The unilateral Laplace transform of tf() (A) s (B) + + (D) (C)
CHAPER SIGNALS & SYSEMS YEAR ONE MARK n n MCQ. If xn [ ] (/) (/) un [ ], hen he region of convergence (ROC) of i z ranform in he z plane will be (A) < z < (B) < z < (C) < z < (D) < z MCQ. he unilaeral
More informationSampling and the Discrete Fourier Transform
Sampling and the Dicrete Fourier Tranform Sampling Method Sampling i mot commonly done with two device, the ample-and-hold (S/H) and the analog-to-digital-converter (ADC) The S/H acquire a CT ignal at
More informationCONTROL SYSTEMS. Chapter 3 Mathematical Modelling of Physical Systems-Laplace Transforms. Prof.Dr. Fatih Mehmet Botsalı
CONTROL SYSTEMS Chaper Mahemaical Modelling of Phyical Syem-Laplace Tranform Prof.Dr. Faih Mehme Boalı Definiion Tranform -- a mahemaical converion from one way of hinking o anoher o make a problem eaier
More informationStudy of simple inductive-capacitive series circuits using MATLAB software package
ecen Advance in ircui, Syem and Auomaic onrol Sudy of imple inducive-capaciive erie circui uing MAAB ofware package NIUESU IU, PĂSUESU DAGOŞ Faculy of Mechanical and Elecrical Engineering Univeriy of Peroani
More information-6 1 kg 100 cm m v 15µm = kg 1 hr s. Similarly Stokes velocity can be determined for the 25 and 150 µm particles:
009 Pearon Educaion, Inc., Upper Saddle Rier, NJ. All righ reered. Thi publicaion i proeced by Copyrigh and wrien periion hould be obained fro he publiher prior o any prohibied reproducion, orage in a
More informationLaplace 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 informationCS4445/9544 Analysis of Algorithms II Solution for Assignment 1
Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he
More informationPlanar Curves out of Their Curvatures in R
Planar Curves ou o Their Curvaures in R Tala Alkhouli Alied Science Dearen Aqaba College Al Balqa Alied Universiy Aqaba Jordan doi: 9/esj6vn6 URL:h://dxdoiorg/9/esj6vn6 Absrac This research ais o inroduce
More informationCSC 364S Notes University of Toronto, Spring, The networks we will consider are directed graphs, where each edge has associated with it
CSC 36S Noe Univeriy of Torono, Spring, 2003 Flow Algorihm The nework we will conider are direced graph, where each edge ha aociaed wih i a nonnegaive capaciy. The inuiion i ha if edge (u; v) ha capaciy
More informationSAMPLING. Sampling is the acquisition of a continuous signal at discrete time intervals and is a fundamental concept in real-time signal processing.
SAMPLING Sampling i the acquiition of a continuou ignal at dicrete time interval and i a fundamental concept in real-time ignal proceing. he actual ampling operation can alo be defined by the figure belo
More informationCHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition.
CHAPTER 8 Forced Equaion and Syem 8 The aplace Tranform and I Invere Tranform from he Definiion 5 5 = b b {} 5 = 5e d = lim5 e = ( ) b {} = e d = lim e + e d b = (inegraion by par) = = = = b b ( ) ( )
More informationThe Purpose of this talk The generation of the high-frequency resonant FEL wave by means of it s low-frequency wave as a pomp wave
The Purpoe of hi alk The generaion of he high-frequency reonan FEL wave y mean of i low-frequency wave a a pomp wave A free elecron laer ha wo reonan frequencie wih : λ 1, = ( 1 ± β β ) λ w In a waveguide:
More informations-domain Circuit Analysis
Domain ircui Analyi Operae direcly in he domain wih capacior, inducor and reior Key feaure lineariy i preerved c decribed by ODE and heir I Order equal number of plu number of Elemenbyelemen and ource
More informationBayesian Designs for Michaelis-Menten kinetics
Bayeian Deign for ichaeli-enen kineic John ahew and Gilly Allcock Deparen of Saiic Univeriy of Newcale upon Tyne.n..ahew@ncl.ac.uk Reference ec. on hp://www.a.ncl.ac.uk/~nn/alk/ile.h Enzyology any biocheical
More informationAlgorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov)
Algorihm and Daa Srucure 2011/ Week Soluion (Tue 15h - Fri 18h No) 1. Queion: e are gien 11/16 / 15/20 8/13 0/ 1/ / 11/1 / / To queion: (a) Find a pair of ube X, Y V uch ha f(x, Y) = f(v X, Y). (b) Find
More informationBiol. 356 Lab 8. Mortality, Recruitment, and Migration Rates
Biol. 356 Lab 8. Moraliy, Recruimen, and Migraion Raes (modified from Cox, 00, General Ecology Lab Manual, McGraw Hill) Las week we esimaed populaion size hrough several mehods. One assumpion of all hese
More information6.003 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 informationM x t = K x F t x t = A x M 1 F t. M x t = K x cos t G 0. x t = A x cos t F 0
Forced oscillaions (sill undaped): If he forcing is sinusoidal, M = K F = A M F M = K cos G wih F = M G = A cos F Fro he fundaenal heore for linear ransforaions we now ha he general soluion o his inhoogeneous
More informationA Novel Hysteresis Control Technique of VSI Based STATCOM R.A.Kantaria 1, Student Member, IEEE, S.K.Joshi 2, K.R.Siddhapura 3
A Novel Hyerei Conrol Technique o VSI Baed STATCOM R.A.Kanaria, Suden Member, IEEE, S.K.Johi, K.R.Siddhapura 3 Abrac:-The Saic Synchronou Compenaor (STATCOM) i increaingly popular in power qualiy applicaion.
More information6 December 2013 H. T. Hoang - www4.hcmut.edu.vn/~hthoang/ 1
Lecure Noe Fundamenal of Conrol Syem Inrucor: Aoc. Prof. Dr. Huynh Thai Hoang Deparmen of Auomaic Conrol Faculy of Elecrical & Elecronic Engineering Ho Chi Minh Ciy Univeriy of Technology Email: hhoang@hcmu.edu.vn
More information5. Stochastic processes (1)
Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly
More informationLAPLACE 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 informationLecture 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 informationString diagrams. a functorial semantics of proofs and programs. Paul-André Melliès. CNRS, Université Paris Denis Diderot.
Sring diagram a uncorial emanic o proo and program Paul-ndré Melliè CNRS, Univerié Pari Deni Didero Hop-in-Lux Luxembourg 17 July 2009 1 Connecing 2-dimenional cobordim and logic 2 Par 1 Caegorie a monad
More informationChapter 4: Applications of Fourier Representations. Chih-Wei Liu
Chapter 4: Application of Fourier Repreentation Chih-Wei Liu Outline Introduction Fourier ranform of Periodic Signal Convolution/Multiplication with Non-Periodic Signal Fourier ranform of Dicrete-ime Signal
More information