Chapter 3: Fourier Representation of Signals and LTI Systems. Chih-Wei Liu

Size: px
Start display at page:

Download "Chapter 3: Fourier Representation of Signals and LTI Systems. Chih-Wei Liu"

Transcription

1 Chapr 3: Fourir Rprsnaion of Signals and LTI Sysms Chih-Wi Liu

2 Oulin Inroducion Complx Sinusoids and Frquncy Rspons Fourir Rprsnaions for Four Classs of Signals Discr-im Priodic Signals Fourir Sris Coninuous-im Priodic Signals Discr-im Nonpriodic Signals Fourir Transform Coninuous-im Nonpriodic Signals Propris of Fourir rprsnaions Linariy and Symmry Propris Convoluion Propry 2 Lc 3 - cwliu@wins..ncu.du.w

3 Oulin Diffrniaion and Ingraion Propris Tim- and Frquncy-Shif Propris Finding Invrs Fourir Transforms Muliplicaion Propry Scaling Propris Parsval Rlaionships Tim-Bandwidh Produc Dualiy 3 Lc 3 - cwliu@wins..ncu.du.w

4 Inroducion In his chapr, w rprsn a signal as a wighd suprposiion of complx sinusoids. AKA Fourir analysis Th wigh associad wih a sinusoid of a givn frquncy rprsns h conribuion of ha sinusoid o h ovrall signal. Four disinc Fourir rprsnaions: 4 Lc 3 - cwliu@wins..ncu.du.w

5 ( ( ( ( ( ( ( H d h d h h x y Frquncy Rspons of LTI Sysm 5 Th rspons of h LTI sysm o a sinusoidal inpu : H{x(= }= H( For discr-im cas, h rspons of h LTI sysm o a sinusoidal inpu n is H{xn= n }= n H( LTI Sysm h( x ( ( ( H h d consan Dpndn on, bu indpndn on h H ( ( ( n n n H h h n h n x n y Dpndn on, bu indpndn on n

6 Frquncy Rspons of LTI Sysm Frquncy rspons of a coninuous-im LTI sysm x( or xn LTI Sysm y( or yn H( h( d H ( h Frquncy rspons of h LTI sysm can also b rprsnd by H( H( arg{ H( } Magniud rspons Phas rspons H ( arg{ H ( } 6

7 Exampl 3. RC Circui Sysm Th impuls rspons of h RC circui sysm is drivd in Exampl.2 as / RC Find an xprssion for h frquncy rspons, and plo h h ( u ( RC magniud and phas rspons. <Sol.> Frquncy rspons: H RC u d RC 7 RC RC RC RC RC RC RC Magniud rspons: H RC 2 RC 2 Phas rspons: arg d H arcanrc Lc 3 - cwliu@wins..ncu.du.w H Low-pass filr

8 Anohr Maning for Frquncy Rspons Th ignfuncion of h LTI sysm (: x( ( LTI Sysm h( x n n Th ign-rprsnaion of h LTI sysm H ( H y( ( ignvalu Indpndn of y n n n n H H 8 By rprsning arbirary signals as wighd suprposiion of ignfuncion, hn M M x a y( H{ x( } a H ( h wighs dscrib h signal as a funcion of frquncy. (frquncy-domain rprsnaion Muliplicaion in frquncy domain, c.f. convoluion in im-domain

9 Fourir Analysis Non-priodic signals hav (coninuous Fourir ransform rprsnaions, whil priodic signals hav (discr Fourir sris rprsnaions. Why Fourir sris rprsnaions for Priodic signals Priodic signal can b considrd as a wighd suprposiion of (priodic complx sinusoids (using priodic signals o consruc a priodic signal Rcall ha h priodic signal has a (fundamnal priod, his implis ha h priod (or frquncy of ach componn sinusoid mus b an ingr mulipl of h signal s fundamnal priod (or frquncy in frquncy-domain analysis, h wighd complx sinusoids loo li a discr sris of wighd frquncy impuls Fourir sris rprsnaion Qusion: Can any a priodic signal b rprsnd or consrucd by a wighd suprposiion of complx sinusoids? 9 Lc 3 - cwliu@wins..ncu.du.w

10 Approximad Priodic Signals n Suppos h signal xˆ n A is approximad o a discr-im priodic signal xn wih fundamnal priod N, whr = 2/N. ( N n Nn n 2n n n Sinc, hr ar only N n disinc sinusoids of h form :.g. =,,, N- Accordingly, w may rwri h signal as xˆ n N A n DTFS ˆ( A x For coninuous-im cas, w hn hav, whr = 2/T is h fundamnal frquncy of priodic signal x( Alhough is priodic, is disinc for disinc Hnc, an infini numbr of disinc rms, i.. xˆ( A FS Lc 3 - cwliu@wins..ncu.du.w

11 Approximaion Error Man-squar rror (MSE prformanc: N 2 MSE xn xn d N n T 2 MSE x ( x ( d T W s h wighs or cofficins A such ha h MSE is minimum Th DTFS and FS cofficins (Fourir analysis achiv h minimum MSE (MMSE prformanc. Lc 3 - cwliu@wins..ncu.du.w

12 Fourir Analysis Why Fourir ransform rprsnaions for Non-priodic signals 2 Using priodic sinusoids (h sam approach o consruc a nonpriodic signal, hr ar no rsricions on h priod (or frquncy of h componn sinusoids hr ar gnrally having a coninuum of frquncis in frquncy-domain analysis Fourir ransform rprsnaion Fourir ransform: Coninuous-im cas xˆ( ( 2 Discr-im cas d FT n xˆ n ( d 2 DTFT Frquncis sparad by an ingr mulipl of 2 ar idnical xˆ n xˆ( A N A n FS DTFS

13 Oulin Inroducion Complx Sinusoids and Frquncy Rspons Fourir Rprsnaions for Four Classs of Signals Discr-im Priodic Signals Coninuous-im Priodic Signals Discr-im Nonpriodic Signals Fourir Transform Coninuous-im Nonpriodic Signals Propris of Fourir rprsnaions Linariy and Symmry Propris Convoluion Propry 3 Lc 3 - cwliu@wins..ncu.du.w

14 Discr-Tim Fourir Sris (DTFS Th DTFS-pair of a priodic signal xn wih fundamnal priod N and fundamnal frquncy =2/N is xn DTFS; N xn N x n N n n n Th DTFS cofficins ar calld h frquncy-domain rprsnaion for xn Th valu drmins h frquncy of h sinusoid associad wih Th DTFS is xac. (Any priodic discr-im signal can b dscribd in rms of DTFS cofficins xacly Th DTFS is h only on of Fourir analysis ha can b valuad and manipulad in compur for a fini s of N numbrs. 4 Lc 3 - cwliu@wins..ncu.du.w

15 Exampl 3.2 DTFS Cofficins Find h frquncy domain rprsnaion of h signal dpicd in Fig <Sol.>. Priod: N = 5 o = 2/5 2. Odd symmry W choos n = 2 o n = 2 3. Fourir cofficin: 5 2 x n 2 n/5 n2 4 / 5 2 / / 5 2 x x x x x 4 / /5 2 /5 { } 5 5 { sin( 2 / 5} 5 Lc 3 - cwliu@wins..ncu.du.w

16 Exampl 3.2 (coni. If w calcula using n = o n = 4: 8 / 2 / / x x x x / 5 x / 5 8 / 5 8 /5 2 2 /5 2 / { sin( 2 / 5} /5 2 /5 { } sinc 5 Th sam xprssion for h DTFS cofficins!!! 6 Lc 3 - cwliu@wins..ncu.du.w

17 Exampl 3.2 (coni. Evn funcion Magniud spcrum of x n arg Odd funcion arg Phas spcrum of xn 7 Lc 3 - cwliu@wins..ncu.du.w

18 Exampl 3.3 Compuaion by Inspcion Drmin h DTFS cofficins of xn = cos (n/3 +, using h mhod of inspcion. <Sol.>. Priod: N = 6 o = 2/6 = /3 2. Using Eulr s formula, xn can b xprssd as ( n ( n 3 3 n n 3 3 xn ( Compar Eq. (3.3 wih h DTFS of Eq. (3. wih o = /3, wrin by summing from = 2 o = 3: xn 3 n / n/3 n/3 n/3 2 2 n/3 3 n 8 DTFS; 3 xn /2, /2,, ohrwis on 2 3 Lc 3 - cwliu@wins..ncu.du.w

19 Exampl 3.4 Find h DTFS cofficins of h N-priodic impuls rain xn nln. l <Sol.>. Priod: N. 2. By (3., w hav N n2 / N N n n N 9 Lc 3 - cwliu@wins..ncu.du.w

20 Exampl 3.6 Find h DTFS cofficins for h N-priodic squar wav givn by <Sol.>. Priod = N, hnc o = 2/N 2. I is convnin o valua DTFS cofficins ovr h inrval n = M o n = NM. 2 x n,, M n M M n N M o o 3. For =, N, 2N,, w hav M 2M,, N, 2N, N N nm For, N, 2N,, w hav N M nm N N M M n n x n nm M (2M n Lc 3 - cwliu@wins..ncu.du.w N,, N nm N, 2N,

21 Exampl 3.6 (coni. M M (2M,, N, 2 N,... N 2M /2 2M 2M /2 2M /2 /2 /2 /2 N N sin 2M / 2 Th numraor and dnominaor of, abov Eq. ar dividd by 2 N sin / 2, N, 2 N, Evn symmry 2 Th DTFS cofficins for h squar wav, assuming a priod N = 5: (a M = 4. (b M = 2.

22 Symmry Propry of DTFS Cofficins If = -, i is insruciv o considr h conribuion of ach rm in N xn n of priod N Assum ha N is vn, so ha N/2 is ingr. o = 2/N Rwri h DTFS cofficins by ling rang from N/2 + o N/2, i.. x n N / 2 N / 2 Dfin nw s of cofficins B n N /2 mn mn n xn N/2 2m m 2 N /2 N n m m n / 2cos 2 cos,, N /2 2,, 2,, N /2 m N /2 xn B cos( n 22 Lc 3 - cwliu@wins..ncu.du.w A similar xprssion may b drivd for N odd.

23 Exampl 3.7 Th conribuion of ach rm in DTFS sris o h squar wav may b illusrad by J dfining h parial-sum approximaion o xn as x J n B cos( n whr J N/2. This approximaion conains h firs 2J + rms cnrd on = in h squar wav abov. Assum a squar wav has priod N = 5 and M = 2. Evalua on priod of h Jh rm and h 2J + rm approximaion for J =, 3, 5, 23, and 25 <Sol.> J = J = 3 23 Lc 3 - cwliu@wins..ncu.du.w

24 J = 5 J = 23 J = 25 Th cofficins B associad wih valus of nar zro rprsn h lowfrquncy or slowly varying faurs in h signal, whil h cofficins associad wih valus of nar N/2 rprsn h high frquncy or rapidly varying faurs in h signal. 24 Lc 3 - cwliu@wins..ncu.du.w

25 Fourir Sris (FS Th DT-pair of a priodic signal x( wih fundamnal priod T and fundamnal frquncy =2/T is 25 x ( FS; x T x( d T a on priod of x( Th FS cofficins ar calld h frquncy-domain rprsnaion for x( Th valu drmins h frquncy of h sinusoid associad wih Th infini sris in x( is no guarand o convrg for all possibl signals. Suppos w dfin xˆ( approach o? x( Lc 3 - cwliu@wins..ncu.du.w If x( is squar ingrabl, hn T T x x 2 d a zro powr in hir diffrncs.

26 Rmars A zro MSE dos no imply ha h wo signals ar qual poinwis. Dirichl s condiions:. x( is boundd 2. x( has a fini numbr of maximum and minima in on priod 3. x( has a fini numbr of disconinuiis in on priod Poinwis convrgnc of ˆx and x( is guarand a all xcp hos corrsponding o disconinuiis saisfying Dirichl s condiions. If x( saisfis Dirichl s condiions and is no coninuous, hn ˆx convrgs o h midpoin of h lf ad righ limis of x( a ach disconinuiy. 26 Lc 3 - cwliu@wins..ncu.du.w

27 Exampl 3.9 Drmin h FS cofficins for h signal x(. <Sol.>. Th priod of x( is T = 2, so o =2/2 =. 2. Ta on priod of x(: x( = 2, 2. Thn d d Th Magniud of h magniud spcrum of x( 27 Lc 3 - cwliu@wins..ncu.du.w Th phas of h phas spcrum of x(

28 Exampl 3. Drmin h FS cofficins for h signal x( dfind by x 4l <Sol.>. Fundamnal priod of x( is T = 4, ach priod conains an impuls. 2. By ingraing ovr a priod ha is symmric abou h origin, 2 < 2, o obain : 2 / d 3. Th magniud spcrum is consan and h phas spcrum is zro. l 28 Lc 3 - cwliu@wins..ncu.du.w

29 Exampl 3. Compuaion by Inspcion Drmin h FS rprsnaion of h signal x 3cos / 2 / 4 <Sol.>. Fundamnal frquncy of x( is o = 2/4= /2, so T = Rwri h x( as /2 /4 /2 /4 3 3 x Compar wih 3 /4, 2 /2 x ( 3 /4, 2, ohrwis /4 /2 /4 /2 /4 29 Lc 3 - cwliu@wins..ncu.du.w /4

30 Exampl 3.2 Invrs FS Find h (im-domain signal x( corrsponding o h FS cofficins Assum ha h fundamnal priod is T=2. <Sol.>. Fundamnal frquncy: o = 2/T=. Thn /2 /2 x ( x /2 /2 x / 2 / 2 / 2 l l l / 2 l / 2 / 2 / 2 / 2 / 2 / 2 3 Lc 3 - cwliu@wins..ncu.du.w

31 Exampl 3.3 Drmin h FS rprsnaion of h squar wav: <Sol.>. Th priod is T, so h fundamnal frquncy o = 2/T. 2. W considr h inrval T/2 T/2 o obain h FS cofficins. Thn ( For, w hav (2 For =, w hav T /2 T x d d T 2T TT /2 TT d T T T T, T 3 2 T 2sinT T T 2 T T,, By mans of L Hôpial s rul 2sinT 2T lim T T 2sin T T

32 Exampl 3.3 (coni. Figur 3.22 Th FS cofficins,, 5 5, for hr squar wavs. (a T o /T = /4. (b T o /T = /6. (c T o /T = / Lc 3 - cwliu@wins..ncu.du.w

33 Sinc Funcion sinc( u sin( u u Maximum of sinc(u is uniy a u =, h zro crossing occur a ingr valus of u, and h ampliud dis off as /u. Th porion of sinc(u bwn h zro crossings a u = is nown as h mainlob of h sinc funcion. Th smallr rippls ousid h mainlob ar rmd sidlobs 33 Lc 3 - cwliu@wins..ncu.du.w

34 Mor on h FS Pairs 34 Th original FS pairs ar dscribd in xponnial form: L s considr h rigonomric form For ral-valud signal x(:, and ( x arg arg ( ( ( x arg arg arg ( arg ( sin( sin(arg cos( cos(arg 2 arg cos( 2 ( ( x ( cos( sin( x B B A Rwri h signal as w hav

35 Trigonomric FS Pair for Ral Signals x ( B B cos( A sin( whr B, B 2 cos(arg 2 R{ } A 2 sin(arg 2 Im{ } Or, if w us rigonomric FS rprsnaion for a ral-valud priodic signal x( wih priod T, hn T 2 T 2 T B xd ( T B x( cos( d T A x( sin( d T 35 Lc 3 - cwliu@wins..ncu.du.w

36 Exampl 3.5 L us find h FS rprsnaion for h oupu y( of h RC circui in rspons o h squar-wav inpu dpicd in Fig. 3.2, assuming ha T o /T = ¼, T = s, and RC =. s. <Sol.>. If h inpu o an LTI sysm is xprssd as a wighd sum of sinusoids (ignfuncions, hn h oupu is also a wighd sum of sinusoids. 2. Inpu: 3. Oupu: FS; 2sin T y x Y H T y H 4. Frquncy rspons of h RC circui: / RC H / RC 5. Subsiuing for H( o wih RC =. s and 36 o = 2, and T o /T = ¼ Y 2 sin / 2

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018

DEPARTMENT 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 information

Revisiting what you have learned in Advanced Mathematical Analysis

Revisiting 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 information

CSE 245: Computer Aided Circuit Simulation and Verification

CSE 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 information

Nikesh Bajaj. Fourier Analysis and Synthesis Tool. Guess.? Question??? History. Fourier Series. Fourier. Nikesh Bajaj

Nikesh 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 information

AN INTRODUCTION TO FOURIER ANALYSIS PROF. VEDAT TAVSANOĞLU

AN 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 information

Elementary Differential Equations and Boundary Value Problems

Elementary 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 information

Fourier. Continuous time. Review. with period T, x t. Inverse Fourier F Transform. x t. Transform. j t

Fourier. 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 information

Chapter 12 Introduction To The Laplace Transform

Chapter 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 information

Circuits and Systems I

Circuits 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 information

Inverse Fourier Transform. Properties of Continuous time Fourier Transform. Review. Linearity. Reading Assignment Oppenheim Sec pp.289.

Inverse 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 information

Introduction to Fourier Transform

Introduction 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 information

fiziks Institute for NET/JRF, GATE, IIT JAM, JEST, TIFR and GRE in PHYSICAL SCIENCES MATEMATICAL PHYSICS SOLUTIONS are

fiziks Institute for NET/JRF, GATE, IIT JAM, JEST, TIFR and GRE in PHYSICAL SCIENCES MATEMATICAL PHYSICS SOLUTIONS are MTEMTICL PHYSICS SOLUTIONS GTE- Q. Considr an ani-symmric nsor P ij wih indics i and j running from o 5. Th numbr of indpndn componns of h nsor is 9 6 ns: Soluion: Th numbr of indpndn componns of h nsor

More information

Review 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( )

Review 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 information

Frequency Response. Lecture #12 Chapter 10. BME 310 Biomedical Computing - J.Schesser

Frequency 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 information

H is equal to the surface current J S

H 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 information

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review

Spring 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 information

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia

Part 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 information

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors

Boyce/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 information

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form:

Let 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 information

10. The Discrete-Time Fourier Transform (DTFT)

10. 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 information

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems Inrucor Soluion for Aignmn Chapr : Tim Domain Anali of LTIC Sm Problm i a 8 x x wih x u,, an Zro-inpu rpon of h m: Th characriic quaion of h LTIC m i i 8, which ha roo a ± j Th zro-inpu rpon i givn b zi

More information

EE 350 Signals and Systems Spring 2005 Sample Exam #2 - Solutions

EE 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 information

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

Lecture 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 information

7.4 QUANTUM MECHANICAL TREATMENT OF FLUCTUATIONS *

7.4 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 information

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac.

Lecture 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 information

Wave Equation (2 Week)

Wave 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 information

Physics 160 Lecture 3. R. Johnson April 6, 2015

Physics 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 information

Midterm exam 2, April 7, 2009 (solutions)

Midterm 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 information

Chapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System

Chapter 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 information

2 T. or T. DSP First, 2/e. This Lecture: Lecture 7C Fourier Series Examples: Appendix C, Section C-2 Various Fourier Series

2 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 information

SOLUTIONS. 1. Consider two continuous random variables X and Y with joint p.d.f. f ( x, y ) = = = 15. Stepanov Dalpiaz

SOLUTIONS. 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 information

Transfer function and the Laplace transformation

Transfer 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 information

Response of LTI Systems to Complex Exponentials

Response 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 information

4.1 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

4.1 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 information

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]

S.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 information

Boyce/DiPrima 9 th ed, Ch 7.8: Repeated Eigenvalues

Boyce/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 information

Fourier Series: main points

Fourier 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 information

5. An object moving along an x-coordinate axis with its scale measured in meters has a velocity of 6t

5. 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 information

General Article Application of differential equation in L-R and C-R circuit analysis by classical method. Abstract

General Article Application of differential equation in L-R and C-R circuit analysis by classical method. Abstract Applicaion of Diffrnial... Gnral Aricl Applicaion of diffrnial uaion in - and C- circui analysis by classical mhod. ajndra Prasad gmi curr, Dparmn of Mahmaics, P.N. Campus, Pokhara Email: rajndraprasadrgmi@yahoo.com

More information

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016

Applied 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 information

Fourier Series and Parseval s Relation Çağatay Candan Dec. 22, 2013

Fourier Series and Parseval s Relation Çağatay Candan Dec. 22, 2013 Fourir Sris nd Prsvl s Rlion Çğy Cndn Dc., 3 W sudy h m problm EE 3 M, Fll3- in som dil o illusr som conncions bwn Fourir sris, Prsvl s rlion nd RMS vlus. Q. ps h signl sin is h inpu o hlf-wv rcifir circui

More information

ANALYSIS IN THE FREQUENCY DOMAIN

ANALYSIS 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 information

Veer 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

Veer 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 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

whereby we can express the phase by any one of the formulas cos ( 3 whereby we can express the phase by any one of the formulas

whereby we can express the phase by any one of the formulas cos ( 3 whereby we can express the phase by any one of the formulas Third In-Class Exam Soluions Mah 6, Profssor David Lvrmor Tusday, 5 April 07 [0] Th vrical displacmn of an unforcd mass on a spring is givn by h 5 3 cos 3 sin a [] Is his sysm undampd, undr dampd, criically

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

Relation between Fourier Series and Transform

Relation 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 information

Copyright 2012 Pearson Education, Inc. Publishing as Prentice Hall.

Copyright 2012 Pearson Education, Inc. Publishing as Prentice Hall. Chapr Rviw 0 6. ( a a ln a. This will qual a if an onl if ln a, or a. + k an (ln + c. Thrfor, a an valu of, whr h wo curvs inrsc, h wo angn lins will b prpnicular. 6. (a Sinc h lin passs hrough h origin

More information

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument

On 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 information

DISCRETE TIME FOURIER TRANSFORM (DTFT)

DISCRETE 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 information

DE Dr. M. Sakalli

DE Dr. M. Sakalli DE-0 Dr. M. Sakalli DE 55 M. Sakalli a n n 0 a Lh.: an Linar g Equaions Hr if g 0 homognous non-homognous ohrwis driving b a forc. You know h quaions blow alrad. A linar firs ordr ODE has h gnral form

More information

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to:

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to: Rfrncs Brnank, B. and I. Mihov (1998). Masuring monary policy, Quarrly Journal of Economics CXIII, 315-34. Blanchard, O. R. Proi (00). An mpirical characrizaion of h dynamic ffcs of changs in govrnmn spnding

More information

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 )

AR(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 information

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT

An 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 information

LaPlace Transform in Circuit Analysis

LaPlace Transform in Circuit Analysis LaPlac Tranform in Circui Analyi Obciv: Calcula h Laplac ranform of common funcion uing h dfiniion and h Laplac ranform abl Laplac-ranform a circui, including componn wih non-zro iniial condiion. Analyz

More information

3(8 ) (8 x x ) 3x x (8 )

3(8 ) (8 x x ) 3x x (8 ) Scion - CHATER -. a d.. b. d.86 c d 8 d d.9997 f g 6. d. d. Thn, = ln. =. =.. d Thn, = ln.9 =.7 8 -. a d.6 6 6 6 6 8 8 8 b 9 d 6 6 6 8 c d.8 6 6 6 6 8 8 7 7 d 6 d.6 6 6 6 6 6 6 8 u u u u du.9 6 6 6 6 6

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

ECE 3TR4 Communication Systems (Winter 2004)

ECE 3TR4 Communication Systems (Winter 2004) ECE 3R4 Communicaion Sysms Winr 4 Dr.. Kirubarajan Kiruba ECE Dparmn CRL-5 iruba@mcmasr.ca www.c.mcmasr.ca/~iruba/3r4/3r4.hml Cours Ovrviw Communicaion Sysms Ovrviw Fourir Sris/ransorm Rviw Signals and

More information

Control System Engineering (EE301T) Assignment: 2

Control 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 information

EE 529 Remote Sensing Techniques. Review

EE 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 information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano Expcaions: Th Basic Prpard by: Frnando Quijano and Yvonn Quijano CHAPTER CHAPTER14 2006 Prnic Hall Businss Publishing Macroconomics, 4/ Olivir Blanchard 14-1 Today s Lcur Chapr 14:Expcaions: Th Basic Th

More information

Problem 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

Problem 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 information

READING ASSIGNMENTS. Signal Processing First. Fourier Transform LECTURE OBJECTIVES. This Lecture: Lecture 23 Fourier Transform Properties

READING 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 information

I) Title: Rational Expectations and Adaptive Learning. II) Contents: Introduction to Adaptive Learning

I) Title: Rational Expectations and Adaptive Learning. II) Contents: Introduction to Adaptive Learning I) Til: Raional Expcaions and Adapiv Larning II) Conns: Inroducion o Adapiv Larning III) Documnaion: - Basdvan, Olivir. (2003). Larning procss and raional xpcaions: an analysis using a small macroconomic

More information

Poisson process Markov process

Poisson 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 information

ECE351: Signals and Systems I. Thinh Nguyen

ECE351: Signals and Systems I. Thinh Nguyen ECE35: Sigals ad Sysms I Thih Nguy FudamalsofSigalsadSysms x Fudamals of Sigals ad Sysms co. Fudamals of Sigals ad Sysms co. x x] Classificaio of sigals Classificaio of sigals co. x] x x] =xt s =x

More information

2. Transfer function. Kanazawa University Microelectronics Research Lab. Akio Kitagawa

2. 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 information

More on FT. Lecture 10 4CT.5 3CT.3-5,7,8. BME 333 Biomedical Signals and Systems - J.Schesser

More 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 information

ANALOG COMMUNICATION (2)

ANALOG 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 information

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if.

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if. Tranform Mhod and Calculu of Svral Variabl H7, p Lcurr: Armin Halilovic KTH, Campu Haning E-mail: armin@dkh, wwwdkh/armin REPETITION bfor h am PART, Tranform Mhod Laplac ranform: L Driv h formula : a L[

More information

FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Introduction and Linear Systems

FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Introduction and Linear Systems FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Inroducion and Linar Sysms David Lvrmor Dparmn of Mahmaics Univrsiy of Maryland 9 Dcmbr 0 Bcaus h prsnaion of his marial in lcur will diffr from

More information

EXERCISE - 01 CHECK YOUR GRASP

EXERCISE - 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 information

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

2.1. 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 information

Voltage 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!

Voltage 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 information

3.4 Repeated Roots; Reduction of Order

3.4 Repeated Roots; Reduction of Order 3.4 Rpd Roos; Rducion of Ordr Rcll our nd ordr linr homognous ODE b c 0 whr, b nd c r consns. Assuming n xponnil soluion lds o chrcrisic quion: r r br c 0 Qudric formul or fcoring ilds wo soluions, r &

More information

Lecture 4: Laplace Transforms

Lecture 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 information

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

UNIT #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 information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1

More information

ECE 145A / 218 C, notes set 1: Transmission Line Properties and Analysis

ECE 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 information

MATH 308: Diff Eqs, BDP10 EXAMPLES [Belmonte, 2019] 1 Introduction 1.1 Basic Mathematical Models; Direction Fields

MATH 308: Diff Eqs, BDP10 EXAMPLES [Belmonte, 2019] 1 Introduction 1.1 Basic Mathematical Models; Direction Fields MATH 308: Diff Eqs, BDP0 EXAMPLES Blmon, 09 Mos problms ar from NSS9 Inroducion Basic Mahmaical Modls; Dircion Filds / Plo a dircion fild for dy/dx = 4x/y (a) Vrify ha h sraigh lins y = ±x ar soluions

More information

Microscopic Flow Characteristics Time Headway - Distribution

Microscopic 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 information

Linear-Phase FIR Transfer Functions. Functions. Functions. Functions. Functions. Functions. Let

Linear-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 information

From Fourier Series towards Fourier Transform

From 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 information

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Slide 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 information

where: u: input y: output x: state vector A, B, C, D are const matrices

where: 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 information

Problem Set #2 Due: Friday April 20, 2018 at 5 PM.

Problem 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 information

ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER 11

ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER 11 8 Jun ANSWERS TO EVEN NUMBERED EXERCISES IN CHAPTER SECTION : INCENTIVE COMPATABILITY Exrcis - Educaional Signaling A yp consulan has a marginal produc of m( ) = whr Θ = {,, 3} Typs ar uniformly disribud

More information

University of Kansas, Department of Economics Economics 911: Applied Macroeconomics. Problem Set 2: Multivariate Time Series Analysis

University of Kansas, Department of Economics Economics 911: Applied Macroeconomics. Problem Set 2: Multivariate Time Series Analysis Univrsiy of Kansas, Dparmn of Economics Economics 9: Applid Macroconomics Problm S : Mulivaria Tim Sris Analysis Unlss sad ohrwis, assum ha shocks (.g. g and µ) ar whi nois in h following qusions.. Considr

More information

Frequency Response. Response of an LTI System to Eigenfunction

Frequency Response. Response of an LTI System to Eigenfunction Frquncy Rsons Las m w Rvsd formal dfnons of lnary and m-nvaranc Found an gnfuncon for lnar m-nvaran sysms Found h frquncy rsons of a lnar sysm o gnfuncon nu Found h frquncy rsons for cascad, fdbac, dffrnc

More information

Double Slits in Space and Time

Double Slits in Space and Time Doubl Slis in Sac an Tim Gorg Jons As has bn ror rcnly in h mia, a am l by Grhar Paulus has monsra an inrsing chniqu for ionizing argon aoms by using ulra-shor lasr ulss. Each lasr uls is ffcivly on an

More information

The transition:transversion rate ratio vs. the T-ratio.

The 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 information

Lecture 2: Current in RC circuit D.K.Pandey

Lecture 2: Current in RC circuit D.K.Pandey Lcur 2: urrn in circui harging of apacior hrough Rsisr L us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R and a ky K in sris. Whn h ky K is swichd on, h charging

More information

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system:

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system: Undrdamd Sysms Undrdamd Sysms nd Ordr Sysms Ouu modld wih a nd ordr ODE: d y dy a a1 a0 y b f If a 0 0, hn: whr: a d y a1 dy b d y dy y f y f a a a 0 0 0 is h naural riod of oscillaion. is h daming facor.

More information

Discussion 06 Solutions

Discussion 06 Solutions STAT Discussion Soluions Spring 8. Th wigh of fish in La Paradis follows a normal disribuion wih man of 8. lbs and sandard dviaion of. lbs. a) Wha proporion of fish ar bwn 9 lbs and lbs? æ 9-8. - 8. P

More information

Module 1-2: LTI Systems. Prof. Ali M. Niknejad

Module 1-2: LTI Systems. Prof. Ali M. Niknejad Modu -: LTI Sysms Prof. Ai M. Niknad Dparmn of EECS Univrsiy of Caifornia, Brky EE 5 Fa 6 Prof. A. M. Niknad LTI Dfiniion Sysm is inar sudid horoughy in 6AB: Sysm is im invarian: Thr is no cock or im rfrnc

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

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

A Condition for Stability in an SIR Age Structured Disease Model with Decreasing Survival Rate

A Condition for Stability in an SIR Age Structured Disease Model with Decreasing Survival Rate A Condiion for abiliy in an I Ag rucurd Disas Modl wih Dcrasing urvival a A.K. upriana, Edy owono Dparmn of Mahmaics, Univrsias Padjadjaran, km Bandung-umng 45363, Indonsia fax: 6--7794696, mail: asupria@yahoo.com.au;

More information

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER A THREE COPARTENT ATHEATICAL ODEL OF LIVER V. An N. Ch. Paabhi Ramacharyulu Faculy of ahmaics, R D collgs, Hanamonda, Warangal, India Dparmn of ahmaics, Naional Insiu of Tchnology, Warangal, India E-ail:

More information