Tunable Lowpass and Highpass Digital Filters. Tunable IIR Digital Filters. We have shown earlier that the 1st-order lowpass transfer function

Size: px
Start display at page:

Download "Tunable Lowpass and Highpass Digital Filters. Tunable IIR Digital Filters. We have shown earlier that the 1st-order lowpass transfer function"

Transcription

1 Tuable IIR Digital Filters Tuable Lowpass a We have escribe earlier two st-orer a two -orer IIR igital trasfer fuctios with tuable frequecy respose characteristics We shall show ow that these trasfer fuctios ca be realie easily usig allpass structures proviig iepeet tuig of the filter parameters We have show earlier that the st-orer lowpass trasfer fuctio α H LP α a the st-orer highpass trasfer fuctio α H HP α are oubly-complemetary pair Tuable Lowpass a Moreover, they ca be expresse as H ) LP [ A ] H ) HP [ A )] Tuable Lowpass a A realiatio of H LP a H HP base o the allpass-base ecompositio is show below H HP where α A α is a st-orer allpass trasfer fuctio The st-orer allpass filter ca be realie usig ay oe of the 4 sigle-multiplier allpass structures escribe earlier 4 Tuable Lowpass a Oe such realiatio is show below i which the -B cutoff frequecy of both lowpass a highpass filters ca be varie simultaeously by chagig the multiplier coefficiet α Tuable Lowpass a Figure below shows the composite magitue resposes of the two filters for two ifferet values of α 0.8 α 0.4 α 0.05 Magitue ω/π

2 Tuable Bapass a Bastop Digital Filters The -orer bapass trasfer fuctio α H BP β α) α a the -orer bastop trasfer fuctio α β H BS β α) α also form a oubly-complemetary pair Tuable Bapass a Bastop Digital Filters Thus, they ca be expresse i the form H ) BP [ A H ) BS [ A ] where α β α) A β α) α is a -orer allpass trasfer fuctio )] 7 8 Tuable Bapass a Bastop Digital Filters A realiatio of H BP a H BS base o the allpass-base ecompositio is show below Tuable Bapass a Bastop Digital Filters The fial structure is as show below 9 The -orer allpass filter is realie usig a cascae sigle-multiplier lattice structure 0 I the above structure, the multiplier β cotrols the ceter frequecy a the multiplier α cotrols the -B bawith Tuable Bapass a Bastop Digital Filters Figure below illustrates the parametric tuig property of the overall structure Magitue β 0.5 α 0.8 α 0.4 α Magitue β 0.8 β 0. Realiatio of a All-pole IIR Trasfer Fuctio Cosier the cascae lattice structure erive earlier for the realiatio of a allpass trasfer fuctio X ω/π ω/π Y

3 A typical lattice two-pair here is as show below W m ) W m S m ) S m Its iput-output relatios are give by Wm Wm km Sm S k W S ) m m m m From the iput-output relatios we erive the chai matrix escriptio of the two-pair: W m k m Wm S ) m k S m m The chai matrix escriptio of the cascae lattice structure is therefore X ) k k k W Y ) k S k k 4 From the above equatio we arrive at X { [ k k) kk] [ k kk k)] k } W ) ) W usig the relatio S W a the relatios k ", k k, The trasfer fuctio W / X is thus a all-pole fuctio with the same eomiator as that of the r-orer allpass fuctio A : W X Gray-Markel Metho A two-step metho to realie a Mth-orer arbitrary IIR trasfer fuctio H PM / DM Step : A itermeiate allpass trasfer M fuctio AM DM )/ DM is realie i the form of a cascae lattice structure 8 Step : A set of iepeet variables are summe with appropriate weights to yiel the esire umerator P M To illustrate the metho, cosier the realiatio of a r-orer trasfer fuctio P p0 H D p p p

4 I the first step, we form a r-orer allpass trasfer fuctio Y / X D )/ D A Realiatio of A has bee illustrate earlier resultig i the structure show below Objective: Sum the iepeet sigal variables Y, S, S, a S with weights { α i } as show below to realie the esire umerator P X Y 9 0 To this e, we first aalye the cascae lattice structure realiig a etermie the trasfer fuctios S / X, S / X, a / X S X Y We have alreay show S X D From the figure it follows that S k ) S " ) S a hece ) " S X D From Slie o. 0, we have S S S " ) S ) ) W S ) ) ) " W S ) From the last equatio we get " W ) S Substitutig W " ) S ) " S ) S i ) S W S we arrive at ) a S ) " ) ) " S ) S [ " ) ] S 4 4

5 From Thus, " ) " ) ) ) S S we observe 5 ) Thus, S X D ote:the umerator of S i / X is precisely the umerator of the allpass trasfer fuctio S A i i W 6 i We ow form Y o X Y S S S α X α X α X 4 X α Substitutig the expressios for the various trasfer fuctios i the above equatio we arrive at α ) Y o α ) α " ) X D α4 7 8 Comparig the umerator of Y o / X with the esire umerator P a equatig like powers of we obtai α α α" α4 p0 α α α p α α p α p Solvig the above equatios we arrive at α α α α p p α p α α " 4 p0 α α α 9 0 5

6 Example- Cosier P H D The correspoig itermeiate allpass trasfer fuctio is give by A D D ) The allpass trasfer fuctio A was realie earlier i the cascae lattice form as show below X Y I the figure, k., k 0 k " Other pertiet coefficiets are: 0.4, 0.8, 0., p, p 0.44, p 0.6, p 0.0, 0 0 Substitutig these coefficiets i α p α p α α p α α α " 4 p0 α α α α 0.0, α 0.5 α 0.765, α The fial realiatio is as show below k , k 0.708, k 0. 4 Tappe Cascae Lattice Realiatio Usig MATLAB Both the pole-ero a the all-pole IIR cascae lattice structures ca be evelope from their prescribe trasfer fuctios usig the M-file tflatc To this e, Program 6_4 ca be employe Tappe Cascae Lattice Realiatio Usig MATLAB The M-file latctf implemets the reverse process a ca be use to verify the structure evelope usig tflatc To this e, Program 8_5 ca be employe 5 6 6

7 7 A arbitrary th-orer FIR trasfer fuctio of the form H p ca be realie as a cascae lattice structure as show below 8 From figure, it follows that Xm X k m m Ym Y k X Y ) m m m m I matrix form the above equatios ca be writte as X ) m k m Xm Y ) m k Ym m where m,,..., 9 Deote X Y H m m, Gm X X ) m 0 0 The it follows from the iput-output relatios of the m-th two-pair that Hm Hm km Gm G k H G ) m m m m From the previous equatio we observe H k, G k where we have use the facts H X / X G Y0 / X0 X0 / X0 It follows from the above that G k ) H G ) is the mirror-image of H 40 ) From the iput-output relatios of the m-th two-pair we obtai for m : H ) ) H k G G k H G ) Sice H a G are st-orer polyomials, it follows from the above that H ) a G are -orer polyomials 4 4 Substitutig G H ) i the two previous equatios we get H H k H ) G k H H ow we ca write G k H H ) [ k ) )] H H H G ) is the mirror-image of H ) ) 7

8 I the geeral case, from the iput-output relatios of the m-th two-pair we obtai Hm H k m m Gm G k H G ) m m m m It ca be easily show by iuctio that G m H ), m,,..., m m, G m is the mirror-image of H m To evelop the sythesis algorithm, we express H m a G m i terms of H m a G m for m,,...,, arrivig at H G { ) )} H k G k ) { k H G k ) )} 4 44 Substitutig the expressios for a G H p ) H 0 p i the first equatio we get { k ) p k H p k p ) p ) k } If we choose k p, the H reuces to a FIR trasfer fuctio of orer a ca be writte i the form H ) p where p k p p, k Cotiuig the above recursio algorithm, all multiplier coefficiets of the cascae lattice structure ca be compute 47 Example- Cosier 4 H From the above, we observe k4 p Usig p 4 4 k p p, k 4 we etermie the coefficiets of H : p 0.79, p.79 p As a result, H 79 Thus, k p Usig p 0.79 p " k p, k we etermie the coefficiets of H : p".0, p.0 " 8

9 As a result, H From the above, we get k " p The fial recursio yiels the last multiplier coefficiet k " p / k) 0.5 The complete realiatio is show below Realiatio Usig MATLAB The M-file tflatc ca be use to compute the multiplier coefficiets of the FIR cascae lattice structure To this e Program 8_7 ca be employe The multiplier coefficiets ca also be etermie usig the M-file polyrc 49 k 0.5, k, k 0.79, k

We have shown earlier that the 1st-order lowpass transfer function

We have shown earlier that the 1st-order lowpass transfer function Tunable IIR Digital Filters We have described earlier two st-order and two nd-order IIR digital transfer functions with tunable frequency response characteristics We shall show now that these transfer

More information

Tunable IIR Digital Filters

Tunable IIR Digital Filters Tunable IIR Digital Filters We have described earlier two st-order and two nd-order IIR digital transfer functions with tunable frequency response characteristics We shall show now that these transfer

More information

Basic IIR Digital Filter Structures

Basic IIR Digital Filter Structures Basic IIR Digital Filter Structures The causal IIR igital filters we are concerne with in this course are characterie by a real rational transfer function of or, equivalently by a constant coefficient

More information

Consider for simplicity a 3rd-order IIR filter with a transfer function. where

Consider for simplicity a 3rd-order IIR filter with a transfer function. where Basic IIR Digital Filter The causal IIR igital filters we are concerne with in this course are characterie by a real rational transfer function of or, equivalently by a constant coefficient ifference equation

More information

Z - Transform. It offers the techniques for digital filter design and frequency analysis of digital signals.

Z - Transform. It offers the techniques for digital filter design and frequency analysis of digital signals. Z - Trasform The -trasform is a very importat tool i describig ad aalyig digital systems. It offers the techiques for digital filter desig ad frequecy aalysis of digital sigals. Defiitio of -trasform:

More information

FIR Filter Design: Part II

FIR Filter Design: Part II EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we cosider how we might go about desigig FIR filters with arbitrary frequecy resposes, through compositio of multiple sigle-peak

More information

EE Midterm Test 1 - Solutions

EE Midterm Test 1 - Solutions EE35 - Midterm Test - Solutios Total Poits: 5+ 6 Bous Poits Time: hour. ( poits) Cosider the parallel itercoectio of the two causal systems, System ad System 2, show below. System x[] + y[] System 2 The

More information

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations ECE-S352 Itroductio to Digital Sigal Processig Lecture 3A Direct Solutio of Differece Equatios Discrete Time Systems Described by Differece Equatios Uit impulse (sample) respose h() of a DT system allows

More information

k=1 s k (x) (3) and that the corresponding infinite series may also converge; moreover, if it converges, then it defines a function S through its sum

k=1 s k (x) (3) and that the corresponding infinite series may also converge; moreover, if it converges, then it defines a function S through its sum 0. L Hôpital s rule You alreay kow from Lecture 0 that ay sequece {s k } iuces a sequece of fiite sums {S } through S = s k, a that if s k 0 as k the {S } may coverge to the it k= S = s s s 3 s 4 = s k.

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

THE LEGENDRE POLYNOMIALS AND THEIR PROPERTIES. r If one now thinks of obtaining the potential of a distributed mass, the solution becomes-

THE LEGENDRE POLYNOMIALS AND THEIR PROPERTIES. r If one now thinks of obtaining the potential of a distributed mass, the solution becomes- THE LEGENDRE OLYNOMIALS AND THEIR ROERTIES The gravitatioal potetial ψ at a poit A at istace r from a poit mass locate at B ca be represete by the solutio of the Laplace equatio i spherical cooriates.

More information

The Z-Transform. (t-t 0 ) Figure 1: Simplified graph of an impulse function. For an impulse, it can be shown that (1)

The Z-Transform. (t-t 0 ) Figure 1: Simplified graph of an impulse function. For an impulse, it can be shown that (1) The Z-Trasform Sampled Data The geeralied fuctio (t) (also kow as the impulse fuctio) is useful i the defiitio ad aalysis of sampled-data sigals. Figure below shows a simplified graph of a impulse. (t-t

More information

Generalizing the DTFT. The z Transform. Complex Exponential Excitation. The Transfer Function. Systems Described by Difference Equations

Generalizing the DTFT. The z Transform. Complex Exponential Excitation. The Transfer Function. Systems Described by Difference Equations Geeraliig the DTFT The Trasform M. J. Roberts - All Rights Reserved. Edited by Dr. Robert Akl 1 The forward DTFT is defied by X e jω = x e jω i which = Ω is discrete-time radia frequecy, a real variable.

More information

Question1 Multiple choices (circle the most appropriate one):

Question1 Multiple choices (circle the most appropriate one): Philadelphia Uiversity Studet Name: Faculty of Egieerig Studet Number: Dept. of Computer Egieerig Fial Exam, First Semester: 2014/2015 Course Title: Digital Sigal Aalysis ad Processig Date: 01/02/2015

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

Mechatronics II Laboratory Exercise 5 Second Order Response

Mechatronics II Laboratory Exercise 5 Second Order Response Mechatroics II Laboratory Exercise 5 Seco Orer Respose Theoretical Backgrou Seco orer ifferetial equatios approximate the yamic respose of may systems. The respose of a geeric seco orer system ca be see

More information

Course Outline. Problem Identification. Engineering as Design. Amme 3500 : System Dynamics and Control. System Response. Dr. Stefan B.

Course Outline. Problem Identification. Engineering as Design. Amme 3500 : System Dynamics and Control. System Response. Dr. Stefan B. Course Outlie Amme 35 : System Dyamics a Cotrol System Respose Week Date Cotet Assigmet Notes Mar Itrouctio 8 Mar Frequecy Domai Moellig 3 5 Mar Trasiet Performace a the s-plae 4 Mar Block Diagrams Assig

More information

Lecture #3. Math tools covered today

Lecture #3. Math tools covered today Toay s Program:. Review of previous lecture. QM free particle a particle i a bo. 3. Priciple of spectral ecompositio. 4. Fourth Postulate Math tools covere toay Lecture #3. Lear how to solve separable

More information

AP Calculus BC Review Chapter 12 (Sequences and Series), Part Two. n n th derivative of f at x = 5 is given by = x = approximates ( 6)

AP Calculus BC Review Chapter 12 (Sequences and Series), Part Two. n n th derivative of f at x = 5 is given by = x = approximates ( 6) AP Calculus BC Review Chapter (Sequeces a Series), Part Two Thigs to Kow a Be Able to Do Uersta the meaig of a power series cetere at either or a arbitrary a Uersta raii a itervals of covergece, a kow

More information

COMM 602: Digital Signal Processing

COMM 602: Digital Signal Processing COMM 60: Digital Sigal Processig Lecture 4 -Properties of LTIS Usig Z-Trasform -Iverse Z-Trasform Properties of LTIS Usig Z-Trasform Properties of LTIS Usig Z-Trasform -ve +ve Properties of LTIS Usig Z-Trasform

More information

University of California at Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences

University of California at Berkeley College of Engineering Department of Electrical Engineering and Computer Sciences A Uiversity of Califoria at Berkeley College of Egieerig Departmet of Electrical Egieerig ad Computer Scieces U N I V E R S T H E I T Y O F LE T TH E R E B E LI G H T C A L I F O R N 8 6 8 I A EECS : Sigals

More information

The z-transform can be used to obtain compact transform-domain representations of signals and systems. It

The z-transform can be used to obtain compact transform-domain representations of signals and systems. It 3 4 5 6 7 8 9 10 CHAPTER 3 11 THE Z-TRANSFORM 31 INTRODUCTION The z-trasform ca be used to obtai compact trasform-domai represetatios of sigals ad systems It provides ituitio particularly i LTI system

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

The Chi Squared Distribution Page 1

The Chi Squared Distribution Page 1 The Chi Square Distributio Page Cosier the istributio of the square of a score take from N(, The probability that z woul have a value less tha is give by z / g ( ( e z if > F π, if < z where ( e g e z

More information

Complex Algorithms for Lattice Adaptive IIR Notch Filter

Complex Algorithms for Lattice Adaptive IIR Notch Filter 4th Iteratioal Coferece o Sigal Processig Systems (ICSPS ) IPCSIT vol. 58 () () IACSIT Press, Sigapore DOI:.7763/IPCSIT..V58. Complex Algorithms for Lattice Adaptive IIR Notch Filter Hog Liag +, Nig Jia

More information

ADVANCED DIGITAL SIGNAL PROCESSING

ADVANCED DIGITAL SIGNAL PROCESSING ADVANCED DIGITAL SIGNAL PROCESSING PROF. S. C. CHAN (email : sccha@eee.hku.hk, Rm. CYC-702) DISCRETE-TIME SIGNALS AND SYSTEMS MULTI-DIMENSIONAL SIGNALS AND SYSTEMS RANDOM PROCESSES AND APPLICATIONS ADAPTIVE

More information

Frequency Response of FIR Filters

Frequency Response of FIR Filters EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we itroduce the idea of the frequecy respose of LTI systems, ad focus specifically o the frequecy respose of FIR filters.. Steady-state

More information

Chapter 7 z-transform

Chapter 7 z-transform Chapter 7 -Trasform Itroductio Trasform Uilateral Trasform Properties Uilateral Trasform Iversio of Uilateral Trasform Determiig the Frequecy Respose from Poles ad Zeros Itroductio Role i Discrete-Time

More information

Exponential Moving Average Pieter P

Exponential Moving Average Pieter P Expoetial Movig Average Pieter P Differece equatio The Differece equatio of a expoetial movig average lter is very simple: y[] x[] + (1 )y[ 1] I this equatio, y[] is the curret output, y[ 1] is the previous

More information

New method for evaluating integrals involving orthogonal polynomials: Laguerre polynomial and Bessel function example

New method for evaluating integrals involving orthogonal polynomials: Laguerre polynomial and Bessel function example New metho for evaluatig itegrals ivolvig orthogoal polyomials: Laguerre polyomial a Bessel fuctio eample A. D. Alhaiari Shura Coucil, Riyah, Saui Arabia AND Physics Departmet, Kig Fah Uiversity of Petroleum

More information

ME 375 FINAL EXAM Friday, May 6, 2005

ME 375 FINAL EXAM Friday, May 6, 2005 ME 375 FINAL EXAM Friay, May 6, 005 Divisio: Kig 11:30 / Cuigham :30 (circle oe) Name: Istructios (1) This is a close book examiatio, but you are allowe three 8.5 11 crib sheets. () You have two hours

More information

Solution of EECS 315 Final Examination F09

Solution of EECS 315 Final Examination F09 Solutio of EECS 315 Fial Examiatio F9 1. Fid the umerical value of δ ( t + 4ramp( tdt. δ ( t + 4ramp( tdt. Fid the umerical sigal eergy of x E x = x[ ] = δ 3 = 11 = ( = ramp( ( 4 = ramp( 8 = 8 [ ] = (

More information

Written exam Digital Signal Processing for BMT (8E070). Tuesday November 1, 2011, 09:00 12:00.

Written exam Digital Signal Processing for BMT (8E070). Tuesday November 1, 2011, 09:00 12:00. Techische Uiversiteit Eidhove Fac. Biomedical Egieerig Writte exam Digital Sigal Processig for BMT (8E070). Tuesday November, 0, 09:00 :00. (oe page) ( problems) Problem. s Cosider a aalog filter with

More information

The structure of Fourier series

The structure of Fourier series The structure of Fourier series Valery P Dmitriyev Lomoosov Uiversity, Russia Date: February 3, 2011) Fourier series is costructe basig o the iea to moel the elemetary oscillatio 1, +1) by the expoetial

More information

Linear time invariant systems

Linear time invariant systems Liear time ivariat systems Alejadro Ribeiro Dept. of Electrical ad Systems Egieerig Uiversity of Pesylvaia aribeiro@seas.upe.edu http://www.seas.upe.edu/users/~aribeiro/ February 25, 2016 Sigal ad Iformatio

More information

Ch3 Discrete Time Fourier Transform

Ch3 Discrete Time Fourier Transform Ch3 Discrete Time Fourier Trasform 3. Show that the DTFT of [] is give by ( k). e k 3. Determie the DTFT of the two sided sigal y [ ],. 3.3 Determie the DTFT of the causal sequece x[ ] A cos( 0 ) [ ],

More information

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and Filter bas Separately, the lowpass ad highpass filters are ot ivertible T removes the highest frequecy / ad removes the lowest frequecy Together these filters separate the sigal ito low-frequecy ad high-frequecy

More information

3. Calculus with distributions

3. Calculus with distributions 6 RODICA D. COSTIN 3.1. Limits of istributios. 3. Calculus with istributios Defiitio 4. A sequece of istributios {u } coverges to the istributio u (all efie o the same space of test fuctios) if (φ, u )

More information

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io Chapter 9 - CD compaio CHAPTER NINE CD-9.2 CD-9.2. Stages With Voltage ad Curret Gai A Geeric Implemetatio; The Commo-Merge Amplifier The advaced method preseted i the text for approximatig cutoff frequecies

More information

Exam. Notes: A single A4 sheet of paper (double sided; hand-written or computer typed)

Exam. Notes: A single A4 sheet of paper (double sided; hand-written or computer typed) Exam February 8th, 8 Sigals & Systems (5-575-) Prof. R. D Adrea Exam Exam Duratio: 5 Mi Number of Problems: 5 Number of Poits: 5 Permitted aids: Importat: Notes: A sigle A sheet of paper (double sided;

More information

Chapter 4 : Laplace Transform

Chapter 4 : Laplace Transform 4. Itroductio Laplace trasform is a alterative to solve the differetial equatio by the complex frequecy domai ( s = σ + jω), istead of the usual time domai. The DE ca be easily trasformed ito a algebraic

More information

Math 475, Problem Set #12: Answers

Math 475, Problem Set #12: Answers Math 475, Problem Set #12: Aswers A. Chapter 8, problem 12, parts (b) ad (d). (b) S # (, 2) = 2 2, sice, from amog the 2 ways of puttig elemets ito 2 distiguishable boxes, exactly 2 of them result i oe

More information

The Method of Least Squares. To understand least squares fitting of data.

The Method of Least Squares. To understand least squares fitting of data. The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve

More information

x[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal.

x[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal. x[ ] x[ ] x[] x[] x[] x[] 9 8 7 6 5 4 3 3 4 5 6 7 8 9 Figure. Graphical represetatio of a discrete-time sigal. From Discrete-Time Sigal Processig, e by Oppeheim, Schafer, ad Buck 999- Pretice Hall, Ic.

More information

MAXIMALLY FLAT FIR FILTERS

MAXIMALLY FLAT FIR FILTERS MAXIMALLY FLAT FIR FILTERS This sectio describes a family of maximally flat symmetric FIR filters first itroduced by Herrma [2]. The desig of these filters is particularly simple due to the availability

More information

Frequency Domain Filtering

Frequency Domain Filtering Frequecy Domai Filterig Raga Rodrigo October 19, 2010 Outlie Cotets 1 Itroductio 1 2 Fourier Represetatio of Fiite-Duratio Sequeces: The Discrete Fourier Trasform 1 3 The 2-D Discrete Fourier Trasform

More information

FIR Filters. Lecture #7 Chapter 5. BME 310 Biomedical Computing - J.Schesser

FIR Filters. Lecture #7 Chapter 5. BME 310 Biomedical Computing - J.Schesser FIR Filters Lecture #7 Chapter 5 8 What Is this Course All About? To Gai a Appreciatio of the Various Types of Sigals ad Systems To Aalyze The Various Types of Systems To Lear the Skills ad Tools eeded

More information

Warped, Chirp Z-Transform: Radar Signal Processing

Warped, Chirp Z-Transform: Radar Signal Processing arped, Chirp Z-Trasform: Radar Sigal Processig by Garimella Ramamurthy Report o: IIIT/TR// Cetre for Commuicatios Iteratioal Istitute of Iformatio Techology Hyderabad - 5 3, IDIA Jauary ARPED, CHIRP Z

More information

2.710 Optics Spring 09 Solutions to Problem Set #3 Due Wednesday, March 4, 2009

2.710 Optics Spring 09 Solutions to Problem Set #3 Due Wednesday, March 4, 2009 MASSACHUSETTS INSTITUTE OF TECHNOLOGY.70 Optics Sprig 09 Solutios to Problem Set #3 Due Weesay, March 4, 009 Problem : Waa s worl a) The geometry or this problem is show i Figure. For part (a), the object

More information

Fall 2011, EE123 Digital Signal Processing

Fall 2011, EE123 Digital Signal Processing Lecture 5 Miki Lustig, UCB September 14, 211 Miki Lustig, UCB Motivatios for Discrete Fourier Trasform Sampled represetatio i time ad frequecy umerical Fourier aalysis requires a Fourier represetatio that

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

LINEAR RECURSION RELATIONS - LESSON FOUR SECOND-ORDER LINEAR RECURSION RELATIONS

LINEAR RECURSION RELATIONS - LESSON FOUR SECOND-ORDER LINEAR RECURSION RELATIONS LINEAR RECURSION RELATIONS - LESSON FOUR SECOND-ORDER LINEAR RECURSION RELATIONS BROTHER ALFRED BROUSSEAU St. Mary's College, Califoria Give a secod-order liear recursio relatio (.1) T. 1 = a T + b T 1,

More information

2D DSP Basics: 2D Systems

2D DSP Basics: 2D Systems - Digital Image Processig ad Compressio D DSP Basics: D Systems D Systems T[ ] y = T [ ] Liearity Additivity: If T y = T [ ] The + T y = y + y Homogeeity: If The T y = T [ ] a T y = ay = at [ ] Liearity

More information

Pipelined and Parallel Recursive and Adaptive Filters

Pipelined and Parallel Recursive and Adaptive Filters VLSI Digital Sigal Processig Systems Pipelied ad Parallel Recursive ad Adaptive Filters La-Da Va 范倫達, Ph. D. Departmet of Computer Sciece Natioal Chiao ug Uiversity aiwa, R.O.C. Fall, 05 ldva@cs.ctu.edu.tw

More information

Composite Hermite and Anti-Hermite Polynomials

Composite Hermite and Anti-Hermite Polynomials Avaces i Pure Mathematics 5 5 87-87 Publishe Olie December 5 i SciRes. http://www.scirp.org/joural/apm http://.oi.org/.436/apm.5.5476 Composite Hermite a Ati-Hermite Polyomials Joseph Akeyo Omolo Departmet

More information

We are mainly going to be concerned with power series in x, such as. (x)} converges - that is, lims N n

We are mainly going to be concerned with power series in x, such as. (x)} converges - that is, lims N n Review of Power Series, Power Series Solutios A power series i x - a is a ifiite series of the form c (x a) =c +c (x a)+(x a) +... We also call this a power series cetered at a. Ex. (x+) is cetered at

More information

Math 155 (Lecture 3)

Math 155 (Lecture 3) Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,

More information

Physics 116A Solutions to Homework Set #9 Winter 2012

Physics 116A Solutions to Homework Set #9 Winter 2012 Physics 116A Solutios to Homework Set #9 Witer 1 1. Boas, problem 11.3 5. Simplify Γ( 1 )Γ(4)/Γ( 9 ). Usig xγ(x) Γ(x + 1) repeatedly, oe obtais Γ( 9) 7 Γ( 7) 7 5 Γ( 5 ), etc. util fially obtaiig Γ( 9)

More information

6.003 Homework #12 Solutions

6.003 Homework #12 Solutions 6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F for

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

MAS160: Signals, Systems & Information for Media Technology. Problem Set 5. DUE: November 3, (a) Plot of u[n] (b) Plot of x[n]=(0.

MAS160: Signals, Systems & Information for Media Technology. Problem Set 5. DUE: November 3, (a) Plot of u[n] (b) Plot of x[n]=(0. MAS6: Sigals, Systems & Iformatio for Media Techology Problem Set 5 DUE: November 3, 3 Istructors: V. Michael Bove, Jr. ad Rosalid Picard T.A. Jim McBride Problem : Uit-step ad ruig average (DSP First

More information

The Phi Power Series

The Phi Power Series The Phi Power Series I did this work i about 0 years while poderig the relatioship betwee the golde mea ad the Madelbrot set. I have fially decided to make it available from my blog at http://semresearch.wordpress.com/.

More information

Difference Equation Construction (1) ENGG 1203 Tutorial. Difference Equation Construction (2) Grow, baby, grow (1)

Difference Equation Construction (1) ENGG 1203 Tutorial. Difference Equation Construction (2) Grow, baby, grow (1) ENGG 03 Tutorial Differece Equatio Costructio () Systems ad Cotrol April Learig Objectives Differece Equatios Z-trasform Poles Ack.: MIT OCW 6.0, 6.003 Newto s law of coolig states that: The chage i a

More information

CALCULUS BASIC SUMMER REVIEW

CALCULUS BASIC SUMMER REVIEW CALCULUS BASIC SUMMER REVIEW NAME rise y y y Slope of a o vertical lie: m ru Poit Slope Equatio: y y m( ) The slope is m ad a poit o your lie is, ). ( y Slope-Itercept Equatio: y m b slope= m y-itercept=

More information

6.451 Principles of Digital Communication II Wednesday, March 9, 2005 MIT, Spring 2005 Handout #12. Problem Set 5 Solutions

6.451 Principles of Digital Communication II Wednesday, March 9, 2005 MIT, Spring 2005 Handout #12. Problem Set 5 Solutions 6.51 Priciples of Digital Commuicatio II Weesay, March 9, 2005 MIT, Sprig 2005 Haout #12 Problem Set 5 Solutios Problem 5.1 (Eucliea ivisio algorithm). (a) For the set F[x] of polyomials over ay fiel F,

More information

EE Control Systems

EE Control Systems Copyright FL Lewis 7 All rights reserved Updated: Moday, November 1, 7 EE 4314 - Cotrol Systems Bode Plot Performace Specificatios The Bode Plot was developed by Hedrik Wade Bode i 1938 while he worked

More information

A COMPUTATIONAL STUDY UPON THE BURR 2-DIMENSIONAL DISTRIBUTION

A COMPUTATIONAL STUDY UPON THE BURR 2-DIMENSIONAL DISTRIBUTION TOME VI (year 8), FASCICULE 1, (ISSN 1584 665) A COMPUTATIONAL STUDY UPON THE BURR -DIMENSIONAL DISTRIBUTION MAKSAY Ştefa, BISTRIAN Diaa Alia Uiversity Politehica Timisoara, Faculty of Egieerig Hueoara

More information

DIGITAL FILTER ORDER REDUCTION

DIGITAL FILTER ORDER REDUCTION DIGITAL FILTER RDER REDUTI VAHID RAISSI DEHKRDI, McGILL UIVERSITY, AADA, vahid@cim.mcgill.ca AMIR G. AGHDAM, RDIA UIVERSITY, AADA, aghdam@ece.cocordia.ca ABSTRAT I this paper, a method is proposed to reduce

More information

6.003 Homework #12 Solutions

6.003 Homework #12 Solutions 6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] (below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F

More information

Induction proofs - practice! SOLUTIONS

Induction proofs - practice! SOLUTIONS Iductio proofs - practice! SOLUTIONS 1. Prove that f ) = 6 + + 15 is odd for all Z +. Base case: For = 1, f 1) = 41) + 1) + 13 = 19. Sice 19 is odd, f 1) is odd - base case prove. Iductive hypothesis:

More information

Digital signal processing: Lecture 5. z-transformation - I. Produced by Qiangfu Zhao (Since 1995), All rights reserved

Digital signal processing: Lecture 5. z-transformation - I. Produced by Qiangfu Zhao (Since 1995), All rights reserved Digital sigal processig: Lecture 5 -trasformatio - I Produced by Qiagfu Zhao Sice 995, All rights reserved DSP-Lec5/ Review of last lecture Fourier trasform & iverse Fourier trasform: Time domai & Frequecy

More information

The Riemann Zeta Function

The Riemann Zeta Function Physics 6A Witer 6 The Riema Zeta Fuctio I this ote, I will sketch some of the mai properties of the Riema zeta fuctio, ζ(x). For x >, we defie ζ(x) =, x >. () x = For x, this sum diverges. However, we

More information

Digital Filter Structures

Digital Filter Structures Chapter 8 Digital Filter Structures 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 8-1 Block Diagram Representation The convolution sum description of an LTI discrete-time system can, in principle, be used to

More information

Run-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE

Run-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE Geeral e Image Coder Structure Motio Video (s 1,s 2,t) or (s 1,s 2 ) Natural Image Samplig A form of data compressio; usually lossless, but ca be lossy Redudacy Removal Lossless compressio: predictive

More information

2.3 Warmup. Graph the derivative of the following functions. Where necessary, approximate the derivative.

2.3 Warmup. Graph the derivative of the following functions. Where necessary, approximate the derivative. . Warmup Grap te erivative of te followig fuctios. Were ecessar, approimate te erivative. Differetiabilit Must a fuctio ave a erivative at eac poit were te fuctio is efie? Or If f a is efie, must f ( a)

More information

BENDING FREQUENCIES OF BEAMS, RODS, AND PIPES Revision S

BENDING FREQUENCIES OF BEAMS, RODS, AND PIPES Revision S BENDING FREQUENCIES OF BEAMS, RODS, AND PIPES Revisio S By Tom Irvie Email: tom@vibratioata.com November, Itrouctio The fuametal frequecies for typical beam cofiguratios are give i Table. Higher frequecies

More information

On triangular billiards

On triangular billiards O triagular billiars Abstract We prove a cojecture of Keyo a Smillie cocerig the oexistece of acute ratioal-agle triagles with the lattice property. MSC-iex: 58F99, 11N25 Keywors: Polygoal billiars, Veech

More information

Chapter 2 Feedback Control Theory Continued

Chapter 2 Feedback Control Theory Continued Chapter Feedback Cotrol Theor Cotiued. Itroductio I the previous chapter, the respose characteristic of simple first ad secod order trasfer fuctios were studied. It was show that first order trasfer fuctio,

More information

NICK DUFRESNE. 1 1 p(x). To determine some formulas for the generating function of the Schröder numbers, r(x) = a(x) =

NICK DUFRESNE. 1 1 p(x). To determine some formulas for the generating function of the Schröder numbers, r(x) = a(x) = AN INTRODUCTION TO SCHRÖDER AND UNKNOWN NUMBERS NICK DUFRESNE Abstract. I this article we will itroduce two types of lattice paths, Schröder paths ad Ukow paths. We will examie differet properties of each,

More information

FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING

FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING Mechaical Vibratios FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING A commo dampig mechaism occurrig i machies is caused by slidig frictio or dry frictio ad is called Coulomb dampig. Coulomb dampig

More information

2D DSP Basics: Systems Stability, 2D Sampling

2D DSP Basics: Systems Stability, 2D Sampling - Digital Iage Processig ad Copressio D DSP Basics: Systes Stability D Saplig Stability ty Syste is stable if a bouded iput always results i a bouded output BIBO For LSI syste a sufficiet coditio for stability:

More information

MEI Casio Tasks for Further Pure

MEI Casio Tasks for Further Pure Task Complex Numbers: Roots of Quadratic Equatios. Add a ew Equatio scree: paf 2. Chage the Complex output to a+bi: LpNNNNwd 3. Select Polyomial ad set the Degree to 2: wq 4. Set a=, b=5 ad c=6: l5l6l

More information

Chapter 8. DFT : The Discrete Fourier Transform

Chapter 8. DFT : The Discrete Fourier Transform Chapter 8 DFT : The Discrete Fourier Trasform Roots of Uity Defiitio: A th root of uity is a complex umber x such that x The th roots of uity are: ω, ω,, ω - where ω e π /. Proof: (ω ) (e π / ) (e π )

More information

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms.

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms. [ 11 ] 1 1.1 Polyomial Fuctios 1 Algebra Ay fuctio f ( x) ax a1x... a1x a0 is a polyomial fuctio if ai ( i 0,1,,,..., ) is a costat which belogs to the set of real umbers ad the idices,, 1,...,1 are atural

More information

Worksheet on Generating Functions

Worksheet on Generating Functions Worksheet o Geeratig Fuctios October 26, 205 This worksheet is adapted from otes/exercises by Nat Thiem. Derivatives of Geeratig Fuctios. If the sequece a 0, a, a 2,... has ordiary geeratig fuctio A(x,

More information

Chapter 8. Euler s Gamma function

Chapter 8. Euler s Gamma function Chapter 8 Euler s Gamma fuctio The Gamma fuctio plays a importat role i the fuctioal equatio for ζ(s that we will derive i the ext chapter. I the preset chapter we have collected some properties of the

More information

SOLUTION SET VI FOR FALL [(n + 2)(n + 1)a n+2 a n 1 ]x n = 0,

SOLUTION SET VI FOR FALL [(n + 2)(n + 1)a n+2 a n 1 ]x n = 0, 4. Series Solutios of Differetial Equatios:Special Fuctios 4.. Illustrative examples.. 5. Obtai the geeral solutio of each of the followig differetial equatios i terms of Maclauri series: d y (a dx = xy,

More information

ELEG3503 Introduction to Digital Signal Processing

ELEG3503 Introduction to Digital Signal Processing ELEG3503 Itroductio to Digital Sigal Processig 1 Itroductio 2 Basics of Sigals ad Systems 3 Fourier aalysis 4 Samplig 5 Liear time-ivariat (LTI) systems 6 z-trasform 7 System Aalysis 8 System Realizatio

More information

Definition of z-transform.

Definition of z-transform. - Trasforms Frequecy domai represetatios of discretetime sigals ad LTI discrete-time systems are made possible with the use of DTFT. However ot all discrete-time sigals e.g. uit step sequece are guarateed

More information

Ultrafast Optical Physics II (SoSe 2017) Lecture 2, April 21

Ultrafast Optical Physics II (SoSe 2017) Lecture 2, April 21 Ultrafast Optical Physics II SoSe 7 Lecture pril Susceptibility a Sellmeier equatio Phase velocity group velocity a ispersio 3 Liear pulse propagatio Maxwell s Equatios of isotropic a homogeeous meia Maxwell

More information

P. Z. Chinn Department of Mathematics, Humboldt State University, Arcata, CA

P. Z. Chinn Department of Mathematics, Humboldt State University, Arcata, CA RISES, LEVELS, DROPS AND + SIGNS IN COMPOSITIONS: EXTENSIONS OF A PAPER BY ALLADI AND HOGGATT S. Heubach Departmet of Mathematics, Califoria State Uiversity Los Ageles 55 State Uiversity Drive, Los Ageles,

More information

POWER SERIES SOLUTION OF FIRST ORDER MATRIX DIFFERENTIAL EQUATIONS

POWER SERIES SOLUTION OF FIRST ORDER MATRIX DIFFERENTIAL EQUATIONS Joural of Applied Mathematics ad Computatioal Mechaics 4 3(3) 3-8 POWER SERIES SOLUION OF FIRS ORDER MARIX DIFFERENIAL EQUAIONS Staisław Kukla Izabela Zamorska Istitute of Mathematics Czestochowa Uiversity

More information

Solution of Linear Constant-Coefficient Difference Equations

Solution of Linear Constant-Coefficient Difference Equations ECE 38-9 Solutio of Liear Costat-Coefficiet Differece Equatios Z. Aliyazicioglu Electrical ad Computer Egieerig Departmet Cal Poly Pomoa Solutio of Liear Costat-Coefficiet Differece Equatios Example: Determie

More information

The z Transform. The Discrete LTI System Response to a Complex Exponential

The z Transform. The Discrete LTI System Response to a Complex Exponential The Trasform The trasform geeralies the Discrete-time Forier Trasform for the etire complex plae. For the complex variable is sed the otatio: jω x+ j y r e ; x, y Ω arg r x + y {} The Discrete LTI System

More information

Discrete-Time Signals and Systems. Discrete-Time Signals and Systems. Signal Symmetry. Elementary Discrete-Time Signals.

Discrete-Time Signals and Systems. Discrete-Time Signals and Systems. Signal Symmetry. Elementary Discrete-Time Signals. Discrete-ime Sigals ad Systems Discrete-ime Sigals ad Systems Dr. Deepa Kudur Uiversity of oroto Referece: Sectios. -.5 of Joh G. Proakis ad Dimitris G. Maolakis, Digital Sigal Processig: Priciples, Algorithms,

More information

Optimum Ordering and Pole-Zero Pairing of the Cascade Form IIR. Digital Filter

Optimum Ordering and Pole-Zero Pairing of the Cascade Form IIR. Digital Filter Optimum Ordering and Pole-Zero Pairing of the Cascade Form IIR Digital Filter There are many possible cascade realiations of a higher order IIR transfer function obtained by different pole-ero pairings

More information

Introduction to Astrophysics Tutorial 2: Polytropic Models

Introduction to Astrophysics Tutorial 2: Polytropic Models Itroductio to Astrophysics Tutorial : Polytropic Models Iair Arcavi 1 Summary of the Equatios of Stellar Structure We have arrived at a set of dieretial equatios which ca be used to describe the structure

More information

Curve Sketching Handout #5 Topic Interpretation Rational Functions

Curve Sketching Handout #5 Topic Interpretation Rational Functions Curve Sketchig Hadout #5 Topic Iterpretatio Ratioal Fuctios A ratioal fuctio is a fuctio f that is a quotiet of two polyomials. I other words, p ( ) ( ) f is a ratioal fuctio if p ( ) ad q ( ) are polyomials

More information

Computing the output response of LTI Systems.

Computing the output response of LTI Systems. Computig the output respose of LTI Systems. By breaig or decomposig ad represetig the iput sigal to the LTI system ito terms of a liear combiatio of a set of basic sigals. Usig the superpositio property

More information

Discrete-time signals and systems See Oppenheim and Schafer, Second Edition pages 8 93, or First Edition pages 8 79.

Discrete-time signals and systems See Oppenheim and Schafer, Second Edition pages 8 93, or First Edition pages 8 79. Discrete-time sigals ad systems See Oppeheim ad Schafer, Secod Editio pages 93, or First Editio pages 79. Discrete-time sigals A discrete-time sigal is represeted as a sequece of umbers: x D fxœg; <

More information