ECE 3TR4 Communication Systems (Winter 2004)
|
|
- Berenice Young
- 6 years ago
- Views:
Transcription
1 ECE 3R4 Communicaion Sysms Winr 4 Dr.. Kirubarajan Kiruba ECE Dparmn CRL-5 iruba@mcmasr.ca
2 Cours Ovrviw Communicaion Sysms Ovrviw Fourir Sris/ransorm Rviw Signals and Sysms Rviw Inroducion o Nois Moivaion or Modulaion Ampliud Modulaion Angl Modulaion Puls Modulaion Muliplxing ransmirs and Rcivrs J Bondy
3 Communicaion Sysms Inormaion Sourc ransmir Channl Rcivr Inormaion Dsinaion Blacbrry Kypad GSM-syl RF Wirlss RF FM Dcor AM.5 Pac Spars Brain Vocal rac Acousic Ears Brain IP Pac SONE Rour Fibr Phoo Diod Rour POS Analog Communicaions 3R4: Inormaion is ncodd in a coninuous ampliud, coninuous im signal. Digial Communicaions 4K4: Inormaion is ncodd ino a discr im squnc wih a quanizd alphab. J Bondy 3
4 Communicaion Channls Channl: h mdium lining h ransmir and rcivr. I is ALWAYS analog in naur. ha is vry communicaion sysm is mor or lss ANALOG. Channl yps Wirlin Channls: us a conduciv mdium o dirc ransmid nrgy o h rcivr: Coppr wir or lphons, xdsl Fibr opic cabl Aluminum inrconncs or ICs Wirlss Channls: Uss an opn propagaion mdium RF or cll phons Undrwar acousic ducs or whals J Bondy 4
5 Channl Impairmns As a ransmid signal propagas i loss idliy in a numbr o ways. his loss o idliy mas h rcivd signal loo vry dirn rom h ransmid signal. Addiiv Nois: hrmal nois, muli-ransmir inrrnc Nois ransmir + Rcivr Muliplicaiv Nois: Rayligh Fading Nois ransmir x Rcivr Convoluion Nois: im-dlay mulipah, rvrbraion ransmir Nois Rcivr J Bondy 5
6 3R4 Objciv Inormaion Sourc ransmir Channl Rcivr Inormaion Dsinaion. How o dsign. aing ino accoun 3. ha will provid a sysm ha is: Rliabl: inormaion rcivd is wha was sn Eicin: No wasul o im, powr or spcrum Simpl: conomical or H/W and S/W and usually Robus J Bondy 6
7 rados in Objcivs mporal Us Spcral Us Powr Us Eicin Simpl H/W Simpl S/W Simpl Rliabl Accuracy & Robusnss J Bondy 7
8 Digial Communicaions Digial Inormaion Sourc N Sourc Encodr Channl Encodr DAC Modulaor h placmn o h DAC and ADC is up o h sysm rquirmns. hy can b anywhr bwn h Inormaion Sourcs and Dsinaion and h Modulaor and Dmodulaor, rspcivly. Channl Digial Inormaion Dsinaion Sourc Dcodr Channl Dcodr ADC DModulaor J Bondy 8
9 Fourir Sris/ransorm Rviw 9
10 Fourir Rviw Fourir Sris and ransorms ry o orm a signal ou o sinusoids. hs sinusoids hav a spciic rquncy and go on orvr. ha is your nic im sris which is rprsnd by poins in im will now b rprsnd by poins in rquncy. his is why w us h rms Fourir domain and rquncy domain inrchangably. Rmindr: a jb a cos b + ja sin b J Bondy
11 Wha ransorm, Whn? Sar Domain Discr or Coninuous Priodic ransorm im Discr Ys DFS im Discr No DF im Coninuous Ys FS im Coninuous No F Frquncy Discr Ys I-DFS Frquncy Discr No I-FS Frquncy Coninuous Ys I-DF Frquncy Coninuous No I-F J Bondy
12 Discr im Fourir Sris DFS: I-DFS: jω X[ ] n < N > x[ n] N jω x[ n] < N > X[ ] N n n X[] and x[n] hav priod N Ω π/n J Bondy
13 3 J Bondy Discr im Fourir ransorm Ω Ω n n j j n x X ] [ ] [ Ω Ω Ω π π π d X n x n j j ] [ DF: I-DFS: X[] has priod π
14 Fourir Sris FS: j X[ ] x < > d I-FS: x X[ ] j o X has priod Ω π/ J Bondy 4
15 Fourir ransorm F: I-F: X x j x d j j X j d π h Fourir ransorm is h gnral ransorm, i can handl priodic and non-priodic signals. For a priodic signal i can b hough o as a ransormaion o h Fourir Sris X j π X[ ] δ n J Bondy 5
16 6 J Bondy Fourir Sris > < j d x X ] [ B o A o d x j d x X > < > < sin cos ] [ X B A X A B X θ θ + an ] [
17 x Fourir Sris Ral Signals X[ ] x cos o d j x sin o d < > < > A B I x is ral valud: A A - B -B - X[ ] x X[] + x X[] + j o X[] + jo jo jo jo X[ ] + X[ ] X[] + A + jb + A + jb jo jo jo jo jo jo A + jb + A jb X[] + A + + jb + jo A cos + B sin X[] + R X[ ] o o x + X [] R X [ j j o ] θ X[] + X[ ] cos + θ J Bondy 7
18 Fourir Sris Ral +Evn/Odd x X [] + x X[] + x X[] + R X [ j j ] θ o R { A jb cos + j sin } A cos + B sin Evn: -, hror B ; Cosin Sris Odd: --, hror A ; Sin Sris o o o o J Bondy 8
19 Cosin Fourir Sris j j cos + Evn Funcion FS F πfs X[ ] X[ ] X j πδ + + πδ Whn is F h coninuous counrpar o πfs? How do h Dla s mov as rquncy changs? J Bondy 9
20 Sin Fourir ransorm j j sin Odd Funcion FS F πfs j j X[ ] X[ ] j X j jπδ + jπδ h Fourir ransorm o an Odd Signal is Odd. Noic h Fourir Domain graph is in jf. I is imaginary. J Bondy
21 DC Fourir ransorm DC Funcion FS F FS j ; F X[ ] X j πδ h F o a signal wih a DC componn is sparabl. h DC componn o a im signal is saisically h MEAN. X j π X[ ] δ J Bondy
22 Dla Fourir ransorm Dla Funcion F FS δ - No Fourir Sris, No Priodic X j jπ jπ δ d h F is only congrun wih h FS or PERIODIC signals. A dla has an ininily sp ris im, hror i has a gra dal o high rquncis J Bondy
23 Puls rain Fourir ransorm X n δ n Funcion wih Priod FS X[ ] j n δ n j π j πn π d or n all d Wha happns in h Frquncy Domain whn h im bwn pulss is shornd? Whn? Whn? δ π J Bondy 3
24 im Window Fourir ransorm, < τ, τ No Priodic No FS sinτ F X j τ Sinc τ sin x Sinc x Sa x rc τ x J Bondy 4
25 Idal Filr Fourir ransorm x Sinc W No Priodic No FS F π, < W X j W π rc, W W W Why is his calld h idal ilr? Noic similariis bwn his and rcangular im window, and how W hr is a counrpar o τ hr in conrolling widh. J Bondy 5
26 riangl Fourir ransorm x, τ, No Priodic No FS < τ τ [ ] Λ F X j τ Sinc τ Sinc squard can nvr b ngaiv. Why ar w inroducing hs signals? hy ar h oundaion o mos analog communicaion signals. τ J Bondy 6
27 Mor Complx Exampl An puls rain wih priod on scond is convolvd wih a im windowing uncion wih iming τ o.5 sconds, o produc a 5% duy cycl squar wav. J Bondy 7
28 Mor Complx Exampl h spcrum o h puls rain is: π X j π δ h spcrum o h squar-wav is: X j τ Sinc τ Convoluion urns ino Muliplicaion in h Frq Domain τ δ π X j X j πτ Sinc his urns ino a lin spcra, and how i changs wih changing h paramrs is vry inormaiv J Bondy 8
29 Consan τ τ Ampliud DECREASES as / Lin spcra rsoluion INCREASES as h nvlop is INDEPENDEN o J Bondy 9
30 Consan τ.5 τ.5 τ Ampliud INCREASES in proporion o au Lin spcra rsoluion is INDEPENDEN o au h spcrum SPREADS as h window shorns!!! IME RESOLUION AND FREQUENCY RESOLUION ARE INVERSELY RELAED!!!!!!!! J Bondy 3
31 h Sampling horm On o h undamnal concps in daling wih h rprsnaion o analog signals in h digial domain is h Nyquis Ra, or Minimum im-bandwidh produc. his law sas h minimum sampl rquncy ncssary o xacly rprsn an analog signal as a digial signal. Sinc on o h main consrains in judging h icincy o a communicaion sysm is spcral icincy, h Nyquis ra orms a larg par o h bac-bon o sysm dsign. A ral-valud band-limid signal having no spcral componns abov a rquncy o B Hz is drmind uniquly by is valus a uniorm inrvals spacd no grar han /B sconds apar J Bondy 3
32 3 J Bondy Sampling horm Considr a signal sampld wih an impuls rain p n s n s n jn s n jn s n F F n F F ransorm Fourir p p,, δ π
33 Sampling horm Visual Band limid signal + spcrum Priodic gaing uncion + spcrum Siz o sampling window conrols nvlop o spcrum, sampl rquncy conrols spacing o original spcrum rplicas J Bondy 33
34 Nyquis Ra Sinc h priodic gaing uncion conrols h cnr o h rplicas and h rplicas ar W W πb wid, hn o ma sur hr is no ovrlap: π W B I h signal is sampld a a lowr ra hr will b ovrlap, and in h inal spcrum you won now i h ovrlappd par is rom h spcrum ha is suppos o b hr or rom h ALIASED par o h spcrum J Bondy 34
35 Signals and Sysms Rviw 35
36 Enrgy and Powr Signal Enrgy E Signal Powr P * d, UNIS [ V s] lim * d, UNIS [ V An nrgy signal canno b a powr signal, nor vic-vrsa o b an nrgy signal: Ampliud As im in ] J Bondy 36
37 37 J Bondy Enrgy and Powr Exampl Find E x x x A A E d A d A E A x φ φ φ φ sin 4 cos cos cos sin sin 4 cos cos / / / / lim lim lim A A A P d A d A P x x φ φ φ φ
38 38 J Bondy Parsval s horm Enrgy calculad in h im domain is qual o nrgy calculad in h Frquncy domain. π π π π π d F F d d F d d F d d d F d d F d F F d j j j j * * * * * * * * * *
39 39 J Bondy Powr Spcral Dnsiy π π d S P d F P / / lim F S d dg du u F du u S G du u F du u S G d F d S lim lim lim lim π π π π π π
40 PSD S is h powr spcral dnsiy uncion, i has unis o powr pr Hz. G is h cumulaiv spcral powr uncion, i h amoun o nrgy in h signal in hos componns lss hn. J Bondy 4
41 4 J Bondy Auocorrlaion { } { } { } { } { } / / * / / / / * / / / / * / / / / * * lim lim lim lim lim lim τ τ τ δ π π π τ τ τ j j j j j R d S IF d d S IF d d d S IF d d d S IF d F F S IF F S + + +
42 Auocorrlaion R τ should loo amiliar in a way. I is quivaln o convolving h uncion wih -. R * τ lim τ τ / / * + τ d + τ d h auocorrlaion uncion is on usd or signal dcion in a bacground o random nois. Whn w g ino random nois i will bcom vry vidn why his is so. J Bondy 4
43 Linar im Invarian Sysms Fundamnal way o dscribing many componns in a communicaion sysm. Modls ilrs, ampliirs and qualizrs vry wll. Modl an LI sysm wih h impuls rspons, h, o h sysm, h rspons o an impuls inpu o h sysm. h Fourir ransorm o h impuls rspons is h rquncy ransr uncion. y h x x h y h τ x τ dτ J Bondy 43
44 im Opraors g -a g +b g/ Wha happns o in h Fourir domain o ach o hs? J Bondy 44
45 Invribiliy LI sysms ar invribl I you can drmin h inpu givn h oupu hn a sysm is calld Invribl Givn inpu x and i s oupu is y: y x Is invrd by z: z ½ y x No invribl: y loor{x}!!! A non-invribl sysm usually maps mulipl poins rom h inpu spac o h sam poin in h oupu spac. J Bondy 45
46 46 J Bondy LI Sysms x h y x y h X H Y X Y H In h rquncy domain h convoluion ingral bcoms a muliplicaion, and vic-vrsa. By assssing h rquncy domain magniud and phas w can s how H can c spciic rquncis dirnly: θ θ θ θ θ θ x h y j j j X H Y X H Y x h y +!!! his is h bginning o h ilring inrpraion
47 LI Sysms h Law o Suprposiion: Givn inpus a and b o sysm x, a linar sysm: xa+xb xa+b Givn inpu a and som scalar consan o sysm x, xc a c xa h Law o im Invarianc: Givn som inpu uncion g and is inpu o a sysm X producs an oupu X{g} I g is shid in im by hn h oupu has h sam shi X{g- } - h Law o Commuaion: Givn som uncion g and g * * g J Bondy 47
48 Idal Filr Inroducion Frquncy Rspons Impuls Rspons Low Pass Filr LPF High Pass Filr HPF BandPass Filr BPF BandSop Filr BSF J Bondy 48
49 Ral Filrs In raliy on canno ma h Bric Wall yp idal ilrs. his is du o h undamnal rado bwn im and rquncy rsoluion. I you hav a jump in h rquncy rspons ha is ininisimally rsolvd, you d nd inini im o rprsn ha. On dals wih ilr spciicaions such as bandwidh, rollo, implmnaion complxiy, passband rippl and so on or mos o his cours, and or many uur courss. I is o gra pracical imporanc o undrsand h rados implici in h im-rquncy bandwidh rado. J Bondy 49
50 Filrs con d Mos ilrs bandwidhs ar dind by h 3 db poin, or whr h rquncy ransr rspons is / lss hn h maximum poin. J Bondy 5
51 Filr runcaion - im On can nvr implmn an idal ilr bcaus h inini rquncy rsoluion rquirs inini im. Wha happns whn you jus g rid o som o h im window? W Ringing Gibbs c Longr im Window, spr rquncy roll-o J Bondy 5
Chapter 3: Fourier Representation of Signals and LTI Systems. Chih-Wei Liu
Chapr 3: Fourir Rprsnaion of Signals and LTI Sysms Chih-Wi Liu Oulin Inroducion Complx Sinusoids and Frquncy Rspons Fourir Rprsnaions for Four Classs of Signals Discr-im Priodic Signals Fourir Sris Coninuous-im
More informationGaussian minimum shift keying systems with additive white Gaussian noise
Indian Journal of ur & Applid hysics Vol. 46, January 8, pp. 65-7 Gaussian minimum shif kying sysms wih addiiv whi Gaussian nois A K Saraf & M Tiwari Dparmn of hysics and Elcronics, Dr Harisingh Gour Vishwavidyalaya,
More informationChapter 12 Introduction To The Laplace Transform
Chapr Inroducion To Th aplac Tranorm Diniion o h aplac Tranorm - Th Sp & Impul uncion aplac Tranorm o pciic uncion 5 Opraional Tranorm Applying h aplac Tranorm 7 Invr Tranorm o Raional uncion 8 Pol and
More informationCSE 245: Computer Aided Circuit Simulation and Verification
CSE 45: Compur Aidd Circui Simulaion and Vrificaion Fall 4, Sp 8 Lcur : Dynamic Linar Sysm Oulin Tim Domain Analysis Sa Equaions RLC Nwork Analysis by Taylor Expansion Impuls Rspons in im domain Frquncy
More information2. Transfer function. Kanazawa University Microelectronics Research Lab. Akio Kitagawa
. ransfr funion Kanazawa Univrsiy Mirolronis Rsarh Lab. Akio Kiagawa . Wavforms in mix-signal iruis Configuraion of mix-signal sysm x Digial o Analog Analog o Digial Anialiasing Digial moohing Filr Prossor
More informationEE 529 Remote Sensing Techniques. Review
59 Rmo Snsing Tchniqus Rviw Oulin Annna array Annna paramrs RCS Polariaion Signals CFT DFT Array Annna Shor Dipol l λ r, R[ r ω ] r H φ ηk Ilsin 4πr η µ - Prmiiviy ε - Prmabiliy
More informationWave Equation (2 Week)
Rfrnc Wav quaion ( Wk 6.5 Tim-armonic filds 7. Ovrviw 7. Plan Wavs in Losslss Mdia 7.3 Plan Wavs in Loss Mdia 7.5 Flow of lcromagnic Powr and h Poning Vcor 7.6 Normal Incidnc of Plan Wavs a Plan Boundaris
More informationH is equal to the surface current J S
Chapr 6 Rflcion and Transmission of Wavs 6.1 Boundary Condiions A h boundary of wo diffrn mdium, lcromagnic fild hav o saisfy physical condiion, which is drmind by Maxwll s quaion. This is h boundary condiion
More informationIntroduction to Fourier Transform
EE354 Signals and Sysms Inroducion o Fourir ransform Yao Wang Polychnic Univrsiy Som slids includd ar xracd from lcur prsnaions prpard y McClllan and Schafr Licns Info for SPFirs Slids his work rlasd undr
More informationUNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS
Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o
More informationREADING ASSIGNMENTS. Signal Processing First. Fourier Transform LECTURE OBJECTIVES. This Lecture: Lecture 23 Fourier Transform Properties
Signl Procssing Firs Lcur 3 Fourir rnsform Propris READING ASSIGNMENS his Lcur: Chpr, Scs. -5 o -9 ls in Scion -9 Ohr Rding: Rciion: Chpr, Scs. - o -9 N Lcurs: Chpr Applicions 3/7/4 3, JH McCllln & RW
More informationPhysics 160 Lecture 3. R. Johnson April 6, 2015
Physics 6 Lcur 3 R. Johnson April 6, 5 RC Circui (Low-Pass Filr This is h sam RC circui w lookd a arlir h im doma, bu hr w ar rsd h frquncy rspons. So w pu a s wav sad of a sp funcion. whr R C RC Complx
More informationCircuits and Systems I
Circuis and Sysms I LECTURE #3 Th Spcrum, Priodic Signals, and h Tim-Varying Spcrum lions@pfl Prof. Dr. Volan Cvhr LIONS/Laboraory for Informaion and Infrnc Sysms Licns Info for SPFirs Slids This wor rlasd
More informationMicroscopic Flow Characteristics Time Headway - Distribution
CE57: Traffic Flow Thory Spring 20 Wk 2 Modling Hadway Disribuion Microscopic Flow Characrisics Tim Hadway - Disribuion Tim Hadway Dfiniion Tim Hadway vrsus Gap Ahmd Abdl-Rahim Civil Enginring Dparmn,
More informationAN INTRODUCTION TO FOURIER ANALYSIS PROF. VEDAT TAVSANOĞLU
A IRODUCIO O FOURIER AALYSIS PROF. VEDA AVSAOĞLU 994 A IRODUCIO O FOURIER AALYSIS ABLE OF COES. HE FOURIER SERIES ---------------------------------------------------------------------3.. Priodic Funcions-----------------------------------------------------------------------3..
More informationChapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System
EE 422G No: Chapr 5 Inrucor: Chung Chapr 5 Th Laplac Tranform 5- Inroducion () Sym analyi inpu oupu Dynamic Sym Linar Dynamic ym: A procor which proc h inpu ignal o produc h oupu dy ( n) ( n dy ( n) +
More informationRevisiting what you have learned in Advanced Mathematical Analysis
Fourir sris Rvisiing wh you hv lrnd in Advncd Mhmicl Anlysis L f x b priodic funcion of priod nd is ingrbl ovr priod. f x cn b rprsnd by rigonomric sris, f x n cos nx bn sin nx n cos x b sin x cosx b whr
More informationLecture 2. Basic Digital Communication Principles
Lcr Basic Principls Signals Basd on class nos by Pro: Amir Asi Basic Digial Commnicaion Principls In his lcr w prsn a rviw abo basic principls in digial commnicaion, som o i yo migh hav sn bor Digial vs.
More informationVoltage v(z) ~ E(z)D. We can actually get to this wave behavior by using circuit theory, w/o going into details of the EM fields!
Considr a pair of wirs idal wirs ngh >, say, infinily long olag along a cabl can vary! D olag v( E(D W can acually g o his wav bhavior by using circui hory, w/o going ino dails of h EM filds! Thr
More informationControl System Engineering (EE301T) Assignment: 2
Conrol Sysm Enginring (EE0T) Assignmn: PART-A (Tim Domain Analysis: Transin Rspons Analysis). Oain h rspons of a uniy fdack sysm whos opn-loop ransfr funcion is (s) s ( s 4) for a uni sp inpu and also
More informationREADING ASSIGNMENTS. Signal Processing First. Problem Solving Skills LECTURE OBJECTIVES. x(t) = cos(αt 2 ) Fourier Series ANALYSIS.
Signal Procssing First Lctur 5 Priodic Signals, Harmonics & im-varying Sinusoids READING ASSIGNMENS his Lctur: Chaptr 3, Sctions 3- and 3-3 Chaptr 3, Sctions 3-7 and 3-8 Nxt Lctur: Fourir Sris ANALYSIS
More informationSlide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS
Slid DIGITAL SIGAL PROCESSIG UIT I DISCRETE TIME SIGALS AD SYSTEM Slid Rviw of discrt-tim signals & systms Signal:- A signal is dfind as any physical quantity that varis with tim, spac or any othr indpndnt
More informationAn Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT
[Typ x] [Typ x] [Typ x] ISSN : 974-7435 Volum 1 Issu 24 BioTchnology 214 An Indian Journal FULL PAPE BTAIJ, 1(24), 214 [15197-1521] A sag-srucurd modl of a singl-spcis wih dnsiy-dpndn and birh pulss LI
More informationFourier Series: main points
BIOEN 3 Lcur 6 Fourir rasforms Novmbr 9, Fourir Sris: mai pois Ifii sum of sis, cosis, or boh + a a cos( + b si( All frqucis ar igr mulipls of a fudamal frqucy, o F.S. ca rprs ay priodic fucio ha w ca
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 informationLecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac.
Lctur 2: Discrt-Tim Signals & Systms Rza Mohammadkhani, Digital Signal Procssing, 2015 Univrsity of Kurdistan ng.uok.ac.ir/mohammadkhani 1 Signal Dfinition and Exampls 2 Signal: any physical quantity that
More informationDigital Signal Processing. Digital Signal Processing READING ASSIGNMENTS. License Info for SPFirst Slides. Fourier Transform LECTURE OBJECTIVES
Digil Signl Procssing Digil Signl Procssing Prof. Nizmin AYDIN nydin@yildiz.du.r hp:www.yildiz.du.r~nydin Lcur Fourir rnsform Propris Licns Info for SPFirs Slids READING ASSIGNMENS his work rlsd undr Criv
More informationsymmetric/hermitian matrices, and similarity transformations
Linar lgbra for Wirlss Communicaions Lcur: 6 Diffrnial quaions, Grschgorin's s circl horm, symmric/hrmiian marics, and similariy ransformaions Ov Edfors Dparmn of Elcrical and Informaion Tchnology Lund
More informationMidterm exam 2, April 7, 2009 (solutions)
Univrsiy of Pnnsylvania Dparmn of Mahmaics Mah 26 Honors Calculus II Spring Smsr 29 Prof Grassi, TA Ashr Aul Midrm xam 2, April 7, 29 (soluions) 1 Wri a basis for h spac of pairs (u, v) of smooh funcions
More informationAR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 )
AR() Procss Th firs-ordr auorgrssiv procss, AR() is whr is WN(0, σ ) Condiional Man and Varianc of AR() Condiional man: Condiional varianc: ) ( ) ( Ω Ω E E ) var( ) ) ( var( ) var( σ Ω Ω Ω Ω E Auocovarianc
More informationEE 350 Signals and Systems Spring 2005 Sample Exam #2 - Solutions
EE 35 Signals an Sysms Spring 5 Sampl Exam # - Soluions. For h following signal x( cos( sin(3 - cos(5 - T, /T x( j j 3 j 3 j j 5 j 5 j a -, a a -, a a - ½, a 3 /j-j -j/, a -3 -/jj j/, a 5 -½, a -5 -½,
More informationInverse Fourier Transform. Properties of Continuous time Fourier Transform. Review. Linearity. Reading Assignment Oppenheim Sec pp.289.
Convrgnc of ourir Trnsform Rding Assignmn Oppnhim Sc 42 pp289 Propris of Coninuous im ourir Trnsform Rviw Rviw or coninuous-im priodic signl x, j x j d Invrs ourir Trnsform 2 j j x d ourir Trnsform Linriy
More informationReview Lecture 5. The source-free R-C/R-L circuit Step response of an RC/RL circuit. The time constant = RC The final capacitor voltage v( )
Rviw Lcur 5 Firs-ordr circui Th sourc-fr R-C/R-L circui Sp rspons of an RC/RL circui v( ) v( ) [ v( 0) v( )] 0 Th i consan = RC Th final capacior volag v() Th iniial capacior volag v( 0 ) Volag/currn-division
More informationLecture 1: Numerical Integration The Trapezoidal and Simpson s Rule
Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -
More informationFourier. Continuous time. Review. with period T, x t. Inverse Fourier F Transform. x t. Transform. j t
Coninuous im ourir rnsform Rviw. or coninuous-im priodic signl x h ourir sris rprsnion is x x j, j 2 d wih priod, ourir rnsform Wh bou priodic signls? W willl considr n priodic signl s priodic signl wih
More informationNikesh Bajaj. Fourier Analysis and Synthesis Tool. Guess.? Question??? History. Fourier Series. Fourier. Nikesh Bajaj
Guss.? ourir Analysis an Synhsis Tool Qusion??? niksh.473@lpu.co.in Digial Signal Procssing School of Elcronics an Communicaion Lovly Profssional Univrsiy Wha o you man by Transform? Wha is /Transform?
More informationCharging of capacitor through inductor and resistor
cur 4&: R circui harging of capacior hrough inducor and rsisor us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R, an inducor of inducanc and a y K in sris.
More informationFrequency Response. Lecture #12 Chapter 10. BME 310 Biomedical Computing - J.Schesser
Frquncy Rspns Lcur # Chapr BME 3 Bimdical Cmpuing - J.Schssr 99 Idal Filrs W wan sudy Hω funcins which prvid frquncy slciviy such as: Lw Pass High Pass Band Pass Hwvr, w will lk a idal filring, ha is,
More informationOutline 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 informationResponse of LTI Systems to Complex Exponentials
3 Fourir sris coiuous-im Rspos of LI Sysms o Complx Expoials Ouli Cosidr a LI sysm wih h ui impuls rspos Suppos h ipu sigal is a complx xpoial s x s is a complx umbr, xz zis a complx umbr h or h h w will
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 informationPart B: Transform Methods. Professor E. Ambikairajah UNSW, Australia
Par B: rasform Mhods Profssor E. Ambikairaah UNSW, Ausralia Chapr : Fourir Rprsaio of Sigal. Fourir Sris. Fourir rasform.3 Ivrs Fourir rasform.4 Propris.4. Frqucy Shif.4. im Shif.4.3 Scalig.4.4 Diffriaio
More informationFrom Fourier Series towards Fourier Transform
From Fourir Sris owards Fourir rasform D D d D, d wh lim Dparm of Elcrical ad Compur Eiri D, d wh lim L s Cosidr a fucio G d W ca xprss D i rms of Gw D G Dparm of Elcrical ad Compur Eiri D G G 3 Dparm
More informationChapter 3. The Fourier Series
Chpr 3 h Fourir Sris Signls in h im nd Frquny Domin INC Signls nd Sysms Chpr 3 h Fourir Sris Eponnil Funion r j ros jsin ) INC Signls nd Sysms Chpr 3 h Fourir Sris Odd nd Evn Evn funion : Odd funion :
More information10. The Discrete-Time Fourier Transform (DTFT)
Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w
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 informationECE 145A / 218 C, notes set 1: Transmission Line Properties and Analysis
class nos, M. Rodwll, copyrighd 9 ECE 145A 18 C, nos s 1: Transmission in Propris and Analysis Mark Rodwll Univrsiy of California, Sana Barbara rodwll@c.ucsb.du 85-893-344, 85-893-36 fax Transmission in
More informationDEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018
DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS Aoc. Prof. Dr. Burak Kllci Spring 08 OUTLINE Th Laplac Tranform Rgion of convrgnc for Laplac ranform Invr Laplac ranform Gomric valuaion
More informationLinear-Phase FIR Transfer Functions. Functions. Functions. Functions. Functions. Functions. Let
It is impossibl to dsign an IIR transfr function with an xact linar-phas It is always possibl to dsign an FIR transfr function with an xact linar-phas rspons W now dvlop th forms of th linarphas FIR transfr
More informationEffect of sampling on frequency domain analysis
LIGO-T666--R Ec sampling n rquncy dmain analysis David P. Nrwd W rviw h wll-knwn cs digial sampling n h rquncy dmain analysis an analg signal, wih mphasis n h cs upn ur masurmns. This discussin llws h
More information7.4 QUANTUM MECHANICAL TREATMENT OF FLUCTUATIONS *
Andri Tokmakoff, MIT Dparmn of Chmisry, 5/19/5 7-11 7.4 QUANTUM MECANICAL TREATMENT OF FLUCTUATIONS * Inroducion and Prviw Now h origin of frquncy flucuaions is inracions of our molcul (or mor approprialy
More informationSpring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review
Spring 6 Procss Dynamics, Opraions, and Conrol.45 Lsson : Mahmaics Rviw. conx and dircion Imagin a sysm ha varis in im; w migh plo is oupu vs. im. A plo migh imply an quaion, and h quaion is usually an
More informationApplied Statistics and Probability for Engineers, 6 th edition October 17, 2016
Applid Saisics and robabiliy for Enginrs, 6 h diion Ocobr 7, 6 CHATER Scion - -. a d. 679.. b. d. 88 c d d d. 987 d. 98 f d.. Thn, = ln. =. g d.. Thn, = ln.9 =.. -7. a., by symmry. b.. d...6. 7.. c...
More informationEE140 Introduction to Communication Systems Lecture 2
EE40 Introduction to Communication Systms Lctur 2 Instructor: Prof. Xiliang Luo ShanghaiTch Univrsity, Spring 208 Architctur of a Digital Communication Systm Transmittr Sourc A/D convrtr Sourc ncodr Channl
More informationANALOG COMMUNICATION (2)
DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING ANALOG COMMUNICATION () Fall 03 Oriinal slids by Yrd. Doç. Dr. Burak Klli Modiid by Yrd. Doç. Dr. Didm Kivan Turli OUTLINE Th Invrs Rlaionship bwn Tim
More informationLecture 4: Laplace Transforms
Lur 4: Lapla Transforms Lapla and rlad ransformaions an b usd o solv diffrnial quaion and o rdu priodi nois in signals and imags. Basially, hy onvr h drivaiv opraions ino mulipliaion, diffrnial quaions
More informationRelation between Fourier Series and Transform
EE 37-3 8 Ch. II: Inro. o Sinls Lcur 5 Dr. Wih Abu-Al-Su Rlion bwn ourir Sris n Trnsform Th ourir Trnsform T is riv from h finiion of h ourir Sris S. Consir, for xmpl, h prioic complx sinl To wih prio
More informationChapter 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 informationElementary Differential Equations and Boundary Value Problems
Elmnar Diffrnial Equaions and Boundar Valu Problms Boc. & DiPrima 9 h Ediion Chapr : Firs Ordr Diffrnial Equaions 00600 คณ ตศาสตร ว ศวกรรม สาขาว ชาว ศวกรรมคอมพ วเตอร ป การศ กษา /55 ผศ.ดร.อร ญญา ผศ.ดร.สมศ
More informationRandom Process Part 1
Random Procss Part A random procss t (, ζ is a signal or wavform in tim. t : tim ζ : outcom in th sampl spac Each tim w rapat th xprimnt, a nw wavform is gnratd. ( W will adopt t for short. Tim sampls
More informationPoisson process Markov process
E2200 Quuing hory and lraffic 2nd lcur oion proc Markov proc Vikoria Fodor KTH Laboraory for Communicaion nwork, School of Elcrical Enginring 1 Cour oulin Sochaic proc bhind quuing hory L2-L3 oion proc
More informationOn the Speed of Heat Wave. Mihály Makai
On h Spd of Ha Wa Mihály Maai maai@ra.bm.hu Conns Formulaion of h problm: infini spd? Local hrmal qulibrium (LTE hypohsis Balanc quaion Phnomnological balanc Spd of ha wa Applicaion in plasma ranspor 1.
More information4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b
4. Th Uniform Disribuion Df n: A c.r.v. has a coninuous uniform disribuion on [a, b] whn is pdf is f x a x b b a Also, b + a b a µ E and V Ex4. Suppos, h lvl of unblivabiliy a any poin in a Transformrs
More informationMixers: Reciprocity N-path designs
c145c lcur nos Mixrs: Rciprociy N-pah dsigns Mark Rodwll, Univrsiy o Caliornia, ana arbara dal mixing is muliplicaion V V ( V cos( ( V cos( V ( V cos( V No h coicin 1/ V 0 cos( / V 0 How do w acually provid
More information2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35
MATH 5 PS # Summr 00.. Diffrnial Equaions and Soluions PS.# Show ha ()C #, 4, 7, 0, 4, 5 ( / ) is a gnral soluion of h diffrnial quaion. Us a compur or calculaor o skch h soluions for h givn valus of h
More informationXV Exponential and Logarithmic Functions
MATHEMATICS 0-0-RE Dirnial Calculus Marin Huard Winr 08 XV Eponnial and Logarihmic Funcions. Skch h graph o h givn uncions and sa h domain and rang. d) ) ) log. Whn Sarah was born, hr parns placd $000
More information5. An object moving along an x-coordinate axis with its scale measured in meters has a velocity of 6t
AP CALCULUS FINAL UNIT WORKSHEETS ACCELERATION, VELOCTIY AND POSITION In problms -, drmin h posiion funcion, (), from h givn informaion.. v (), () = 5. v ()5, () = b g. a (), v() =, () = -. a (), v() =
More informationANALYSIS IN THE FREQUENCY DOMAIN
ANALYSIS IN THE FREQUENCY DOMAIN SPECTRAL DENSITY Dfinition Th spctral dnsit of a S.S.P. t also calld th spctrum of t is dfind as: + { γ }. jτ γ τ F τ τ In othr words, of th covarianc function. is dfind
More informationHomework #2: CMPT-379 Distributed on Oct 2; due on Oct 16 Anoop Sarkar
Homwork #2: CMPT-379 Disribud on Oc 2 du on Oc 16 Anoop Sarkar anoop@cs.su.ca Rading or his homwork includs Chp 4 o h Dragon book. I ndd, rr o: hp://ldp.org/howto/lx-yacc-howto.hml Only submi answrs or
More informationGuest 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 informationECE Connections: What do Roots of Unity have to do with OP-AMPs? Louis Scharf, Colorado State University PART 1: Why Complex?
ECE Conncion: Wha do Roo of Uni hav o do wih OP-AMP? Loui Scharf, Colorado Sa Univri PART : Wh Compl?. Curioi, M favori curioi i : π π ( ) 0.07... π π ECE Conncion: Colorado Sa Univri Ocobr 007 . Quion,
More information( ) C R. υ in RC 1. cos. ,sin. ω ω υ + +
Oscillaors. Thory of Oscillaions. Th lad circui, h lag circui and h lad-lag circui. Th Win Bridg oscillaor. Ohr usful oscillaors. Th 555 Timr. Basic Dscripion. Th S flip flop. Monosabl opraion of h 555
More informationEXERCISE - 01 CHECK YOUR GRASP
DIFFERENTIAL EQUATION EXERCISE - CHECK YOUR GRASP 7. m hn D() m m, D () m m. hn givn D () m m D D D + m m m m m m + m m m m + ( m ) (m ) (m ) (m + ) m,, Hnc numbr of valus of mn will b. n ( ) + c sinc
More informationLet s look again at the first order linear differential equation we are attempting to solve, in its standard form:
Th Ingraing Facor Mhod In h prvious xampls of simpl firs ordr ODEs, w found h soluions by algbraically spara h dpndn variabl- and h indpndn variabl- rms, and wri h wo sids of a givn quaion as drivaivs,
More informationThe transition:transversion rate ratio vs. the T-ratio.
PhyloMah Lcur 8 by Dan Vandrpool March, 00 opics of Discussion ransiion:ransvrsion ra raio Kappa vs. ransiion:ransvrsion raio raio alculaing h xpcd numbr of subsiuions using marix algbra Why h nral im
More informationTransfer function and the Laplace transformation
Lab No PH-35 Porland Sa Univriy A. La Roa Tranfr funcion and h Laplac ranformaion. INTRODUTION. THE LAPLAE TRANSFORMATION L 3. TRANSFER FUNTIONS 4. ELETRIAL SYSTEMS Analyi of h hr baic paiv lmn R, and
More informationFourier Techniques Chapters 2 & 3, Part I
Fourir chiqus Chaprs & 3, Par I Dr. Yu Q. Shi Dp o Elcrical & Compur Egirig Nw Jrsy Isiu o chology Email: shi@i.du usd or h cours: , 4 h Ediio, Lahi ad Dog, Oord
More informationBoyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors
Boc/DiPrima 9 h d, Ch.: Linar Equaions; Mhod of Ingraing Facors Elmnar Diffrnial Equaions and Boundar Valu Problms, 9 h diion, b William E. Boc and Richard C. DiPrima, 009 b John Wil & Sons, Inc. A linar
More informationOn the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument
Inrnaional Rsarch Journal of Applid Basic Scincs 03 Aailabl onlin a wwwirjabscom ISSN 5-838X / Vol 4 (): 47-433 Scinc Eplorr Publicaions On h Driais of Bssl Modifid Bssl Funcions wih Rspc o h Ordr h Argumn
More informationDISCRETE TIME FOURIER TRANSFORM (DTFT)
DISCRETE TIME FOURIER TRANSFORM (DTFT) Th dicrt-tim Fourir Tranform x x n xn n n Th Invr dicrt-tim Fourir Tranform (IDTFT) x n Not: ( ) i a complx valud continuou function = π f [rad/c] f i th digital
More informationIf we integrate the given modulating signal, m(t), we arrive at the following FM signal:
Part b If w intgrat th givn odulating signal, (, w arriv at th following signal: ( Acos( πf t + β sin( πf W can us anothr trigonotric idntity hr. ( Acos( β sin( πf cos( πf Asin( β sin( πf sin( πf Now,
More informationFinal Exam : Solutions
Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b
More informationMore on FT. Lecture 10 4CT.5 3CT.3-5,7,8. BME 333 Biomedical Signals and Systems - J.Schesser
Mr n FT Lcur 4CT.5 3CT.3-5,7,8 BME 333 Bimdicl Signls nd Sysms - J.Schssr 43 Highr Ordr Diffrniin d y d x, m b Y b X N n M m N M n n n m m n m n d m d n m Y n d f n [ n ] F d M m bm m X N n n n n n m p
More information2 T. or T. DSP First, 2/e. This Lecture: Lecture 7C Fourier Series Examples: Appendix C, Section C-2 Various Fourier Series
DSP Firs, Lcur 7C Fourir Sris Empls: Common Priodic Signls READIG ASSIGMES his Lcur: Appndi C, Scion C- Vrious Fourir Sris Puls Wvs ringulr Wv Rcifid Sinusoids lso in Ch. 3, Sc. 3-5 Aug 6 3-6, JH McCllln
More informationProblem 2. Describe the following signals in terms of elementary functions (δ, u,r, ) and compute. x(t+2) x(2-t) RT_1[x] -3-2 = 1 2 = 1
EEE 03, HW NAME: SOLUTIONS Problm. Considr h signal whos graph is shown blow. Skch h following signals:, -, RT [], whr R dnos h rflcion opraion and T 0 dnos shif dlay opraion by 0. - RT_[] - -3 - Problm.
More informationMEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control
MEM 355 Prformanc Enhancmn of Dynamical Sysms A Firs Conrol Problm - Cruis Conrol Harry G. Kwany Darmn of Mchanical Enginring & Mchanics Drxl Univrsiy Cruis Conrol ( ) mv = F mg sinθ cv v +.2v= u 9.8θ
More informationS.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]
S.Y. B.Sc. (IT) : Sm. III Applid Mahmaics Tim : ½ Hrs.] Prlim Qusion Papr Soluion [Marks : 75 Q. Amp h following (an THREE) 3 6 Q.(a) Rduc h mari o normal form and find is rank whr A 3 3 5 3 3 3 6 Ans.:
More informationVeer Surendra Sai University of Technology, Burla. S u b j e c t : S i g n a l s a n d S y s t e m s - I S u b j e c t c o d e : B E E
Vr Surndra Sai Univriy of Tchnology, Burla Dparmn o f E l c r i c a l & E l c r o n i c E n g g S u b j c : S i g n a l a n d S y m - I S u b j c c o d : B E E - 6 0 5 B r a n c h m r : E E E 5 h m SYLLABUS
More informationAli Karimpour Associate Professor Ferdowsi University of Mashhad. Reference: System Identification Theory For The User Lennart Ljung
SYSEM IDEIFICAIO Ali Karimpour Associa Prossor Frdowsi Univrsi o Mashhad Rrnc: Ssm Idniicaion hor For h Usr Lnnar Ljung Lcur 7 lcur 7 Paramr Esimaion Mhods opics o b covrd includ: Guiding Principls Bhind
More informationInstitute of Actuaries of India
Insiu of Acuaris of India ubjc CT3 Probabiliy and Mahmaical aisics Novmbr Examinaions INDICATIVE OLUTION Pag of IAI CT3 Novmbr ol. a sampl man = 35 sampl sandard dviaion = 36.6 b for = uppr bound = 35+*36.6
More informationSinusoidal Response Notes
ECE 30 Sinusoidal Rspons Nots For BIBO Systms AStolp /29/3 Th sinusoidal rspons of a systm is th output whn th input is a sinusoidal (which starts at tim 0) Systm Sinusoidal Rspons stp input H( s) output
More informationAnnounce. ECE 2026 Summer LECTURE OBJECTIVES READING. LECTURE #3 Complex View of Sinusoids May 21, Complex Number Review
ECE 06 Summr 018 Announc HW1 du at bginning of your rcitation tomorrow Look at HW bfor rcitation Lab 1 is Thursday: Com prpard! Offic hours hav bn postd: LECTURE #3 Complx Viw of Sinusoids May 1, 018 READIG
More information2. The Laplace Transform
Th aac Tranorm Inroucion Th aac ranorm i a unamna an vry uu oo or uying many nginring robm To in h aac ranorm w conir a comx variab σ, whr σ i h ra ar an i h imaginary ar or ix vau o σ an w viw a a oin
More informationProblem Set #2 Due: Friday April 20, 2018 at 5 PM.
1 EE102B Spring 2018 Signal Procssing and Linar Systms II Goldsmith Problm St #2 Du: Friday April 20, 2018 at 5 PM. 1. Non-idal sampling and rcovry of idal sampls by discrt-tim filtring 30 pts) Considr
More informationBoyce/DiPrima 9 th ed, Ch 7.8: Repeated Eigenvalues
Boy/DiPrima 9 h d Ch 7.8: Rpad Eignvalus Elmnary Diffrnial Equaions and Boundary Valu Problms 9 h diion by William E. Boy and Rihard C. DiPrima 9 by John Wily & Sons In. W onsidr again a homognous sysm
More informationwhere: u: input y: output x: state vector A, B, C, D are const matrices
Sa pac modl: linar: y or in om : Sa q : f, u Oupu q : y h, u u Du F Gu y H Ju whr: u: inpu y: oupu : a vcor,,, D ar con maric Eampl " $ & ' " $ & 'u y " & * * * * [ ],, D H D I " $ " & $ ' " & $ ' " &
More informationRepresenting 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 informationDSP-First, 2/e. LECTURE # CH2-3 Complex Exponentials & Complex Numbers TLH MODIFIED. Aug , JH McClellan & RW Schafer
DSP-First, / TLH MODIFIED LECTURE # CH-3 Complx Exponntials & Complx Numbrs Aug 016 1 READING ASSIGNMENTS This Lctur: Chaptr, Scts. -3 to -5 Appndix A: Complx Numbrs Complx Exponntials Aug 016 LECTURE
More informationSOLUTIONS. 1. Consider two continuous random variables X and Y with joint p.d.f. f ( x, y ) = = = 15. Stepanov Dalpiaz
STAT UIUC Pracic Problms #7 SOLUTIONS Spanov Dalpiaz Th following ar a numbr of pracic problms ha ma b hlpful for compling h homwor, and will lil b vr usful for suding for ams.. Considr wo coninuous random
More informationChemistry 988 Part 1
Chmisry 988 Par 1 Radiaion Dcion & Masurmn Dp. of Chmisry --- Michigan Sa Univ. aional Suprconducing Cycloron Lab DJMorrissy Spring/2oo9 Cours informaion can b found on h wbsi: hp://www.chmisry.msu.du/courss/cm988uclar/indx.hml
More information