We have shown earlier that the 1st-order lowpass transfer function
|
|
- Nickolas Grant
- 5 years ago
- Views:
Transcription
1 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 functions can be realied easily using allpass structures providing independent tuning of the filter parameters We have shown earlier that the st-order lowpass transfer function + H LP and the st-order highpass transfer function + H HP are doubly-complementary pair Moreover, they can be expressed as H ) LP [ + A ] H ) HP [ A where + A is a st-order allpass transfer function )] A realiation of H LP and H HP based on the allpass-based decomposition is shown below H HP The st-order allpass filter can be realied using any one of the 4single-multiplier allpass structures described earlier 4 One such realiation is shown below in which the -db cutoff frequency of both lowpass and highpass filters can be varied simultaneously by changing the multiplier coefficient Figure below shows the composite magnitude responses of the two filters for two different values of Magnitude ω/π
2 Tunable Bandpass and The nd-order bandpass transfer function H BP β + ) + and the nd-order bandstop transfer function + β + H BS β + ) + also form a doubly-complementary pair Tunable Bandpass and Thus, they can be expressed in the form [ A )] H BP H ) BS [ + A ] where β + ) + A β + ) + is a nd-order allpass transfer function 7 8 Tunable Bandpass and A realiation of H BP and H BS based on the allpass-based decomposition is shown below Tunable Bandpass and The final structure is as shown below 9 The nd-order allpass filter is realied using a cascaded single-multiplier lattice structure 0 In the above structure, the multiplier β controls the center frequency and the multiplier controls the -db bandwidth Tunable Bandpass and Figure below illustrates the parametric tuning property of the overall structure Magnitude β Magnitude β 0.8 β 0. Realiation of an All-pole IIR Transfer Function Consider the cascaded lattice structure derived earlier for the realiation of an allpass transfer function ω/π ω/π
3 A typical lattice two -pair here is as shown below W m+ ) W m S m+ ) S m Its input-output relations are given by Wm Wm + km Sm S k W S ) m+ m m + m 4 From the input-output relations we derive the chain matrix description of the two -pair: W + ) i ki Wi S + ) i k S i i The chain matrix description of the cascaded lattice structure is therefore X ) k k k W Y ) k S k k From the above equation we arrive at X { + [ k + k ) + kk] + + [ k + kk + k)] k } W + d + d + d ) W using the relation S W and the relations " k d, k d k d, The transfer function W / X is thus an all-pole function with the same denominator as that of the rd-orderallpass function A : W X + d + d + d Gray-Markel Method A two -step method to realie an Mth-order arbitrary IIR transfer function H P / D M Step : An intermediate allpass transfer M function AM DM ) / DM is realied in the form of a cascaded lattice structure M 8 Step : A set of independent variables are summed with appropriate weights to yield the desired numerator P M To illustrate the method, consider the realiation of a rd-order transfer function P p0 + H D + d p + + d p + + d p
4 In the first step, we form a rd-order allpass transfer function Y / X D )/ D A Realiation of A has been illustrated earlier resulting in the structure shown below Objective: Sum the independent signal variables Y, S, S, and S with weights { i } as shown below to realie the desired numerator P 9 0 To this end, we first analye the cascaded lattice structure realiing and determine the transfer functions S / X, S / X, and / X S X Y We have already shown S X D From the figure it follows that S k + ) S d" + ) S and hence ) " S d + X D In a similar manner it can be shown that + S ) d + d ) S Thus, ) S d + d + X D ote: The numerator of S i / X is precisely the numerator of the allpass transfer function A S / W i i i 4 We now form Y o Y S S S X + X + X + X 4 X 4
5 Substituting the expressions for the various transfer functions in the above equation we arrive at d + d + d + ) " Y o + d + d + ) + d + ) + X D 4 Comparing the numerator of Y o / X with the desired numerator P and equating like powers of we obtain d + d " + d + 4 p0 d + d + p d + p p 5 6 Solving the above equations we arrive at p p d p d d " 4 p0 d d d Example - Consider P H D The corresponding intermediate allpass transfer function is given by A D D ) The allpass transfer function A was realied earlier in the cascaded lattice form as shown below X Y In the figure, k d 0., k d k " d Other pertinent coefficients are: d 0.4, d 0.8, d 0., d p, p 0.44, p 0.6, p 0.0, 0 0 Substituting these coefficients in p p d p d d " 4 p0 d d d 5
6 Tapped Cascaded Lattice Realiation Using MATLAB 0.0, , The final realiation is as shown below Both the pole-ero and the all-pole IIR cascaded lattice structures can be developed from their prescribed transfer functions using the M-file tflatc To this end, Program 6_4 can be employed k , k 0.708, k 0. Tapped Cascaded Lattice Realiation Using MATLAB The M-file latctf implements the reverse process and can be used to verify the structure developed using tflatc To this end, Program 6_5 can be employed An arbitrary th-order FIR transfer function of the form n H + n pn can be realied as a cascaded lattice structure as shown below 4 5 From figure, it follows that X X k m m + m Ym ) Ym km Xm + Ym In matrix form the above equations can be written as X ) m km Xm Y ) m k Ym m where m,,..., 6 Denote X H m m, Gm X Ym X ) 0 0 Then it follows from the input-output relations of the m-th two-pair that Hm Hm + km Gm G k H G ) m m m + m 6
7 7 From the previous equation we observe H + k, G k + where we have used 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 8 From the input-output relations of the m-th two-pair we obtain for m : H ) ) H + k G G k H + G ) Since H and G are st-order polynomials, it follows from the above that H ) and G are nd-order polynomials 9 Substituting G ) H ) in the two previous equations we get H H + k H ) G k H + H ow we can write G k H + H ) [ k ) )] H + H H G ) is the mirror-image of H ) ) 40 In the general case, from the input-output relations of the m-thtwo-pair we obtain Hm H k m + m Gm G k H G ) m m m + m It can be easily shown by induction that m Gm Hm ), m,,...,, G m is the mirror-image of H m 4 To develop the synthesis algorithm, we express H and G m m ) in terms of H m and G m for m,,...,, arriving at H G { H k G } k ) { k H G + k ) )} Substituting the expressions for n H + n pn and n G H ) n 0 pn + in the first equation we get + { k ) p n pn knp k H ) n n + p ) k } 4 7
8 4 If we choose k p, then H reduces to an FIR transfer function of order and can be written in the form + n H n pn where pn k p n pn, n k Continuing the above recursion algorithm, all multiplier coefficients of the cascaded lattice structure can be computed 44 Example - Consider 4 H From the above, we observe k4 p Using pn 4 4 k p n p, n n k4 we determine the coefficients of H : p 0.79, p.79 p As a result, H Thus, k p 0.79 Using p " n k p n p, n n k we determine the coefficients of H : p".0, p.0 " 46 As a result, H + + From the above, we get k " p The final recursion yields the last multiplier coefficient k p " / + k) 0.5 The complete realiation is shown below k 0.5, k, k 0.79, k Realiation Using MATLAB The M-filetflatc can be used to compute the multiplier coefficients of the FIR cascaded lattice structure To this end Program 6_6 can be employed The multiplier coefficients can also be determined using the M-file polyrc 47 8
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 informationTunable Lowpass and Highpass Digital Filters. Tunable IIR Digital Filters. We have shown earlier that the 1st-order lowpass transfer function
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
More informationDigital 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 informationOptimum 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 informationOptimum Ordering and Pole-Zero Pairing. Optimum Ordering and Pole-Zero Pairing Consider the scaled cascade structure shown below
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 and ordering Each one
More informationBasic 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 informationResponses of Digital Filters Chapter Intended Learning Outcomes:
Responses of Digital Filters Chapter Intended Learning Outcomes: (i) Understanding the relationships between impulse response, frequency response, difference equation and transfer function in characterizing
More informationConsider 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 informationPerfect Reconstruction Two- Channel FIR Filter Banks
Perfect Reconstruction Two- Channel FIR Filter Banks A perfect reconstruction two-channel FIR filter bank with linear-phase FIR filters can be designed if the power-complementary requirement e jω + e jω
More informationDigital Signal Processing:
Digital Signal Processing: Mathematical and algorithmic manipulation of discretized and quantized or naturally digital signals in order to extract the most relevant and pertinent information that is carried
More informationECE503: Digital Signal Processing Lecture 6
ECE503: Digital Signal Processing Lecture 6 D. Richard Brown III WPI 20-February-2012 WPI D. Richard Brown III 20-February-2012 1 / 28 Lecture 6 Topics 1. Filter structures overview 2. FIR filter structures
More informationDigital Filter Structures. Basic IIR Digital Filter Structures. of an LTI digital filter is given by the convolution sum or, by the linear constant
Digital Filter Chapter 8 Digital Filter Block Diagram Representation Equivalent Basic FIR Digital Filter Basic IIR Digital Filter. Block Diagram Representation In the time domain, the input-output relations
More informationQuadrature-Mirror Filter Bank
Quadrature-Mirror Filter Bank In many applications, a discrete-time signal x[n] is split into a number of subband signals { v k [ n]} by means of an analysis filter bank The subband signals are then processed
More informationLet H(z) = P(z)/Q(z) be the system function of a rational form. Let us represent both P(z) and Q(z) as polynomials of z (not z -1 )
Review: Poles and Zeros of Fractional Form Let H() = P()/Q() be the system function of a rational form. Let us represent both P() and Q() as polynomials of (not - ) Then Poles: the roots of Q()=0 Zeros:
More information(Refer Slide Time: )
Digital Signal Processing Prof. S. C. Dutta Roy Department of Electrical Engineering Indian Institute of Technology, Delhi FIR Lattice Synthesis Lecture - 32 This is the 32nd lecture and our topic for
More informationLINEAR-PHASE FIR FILTERS DESIGN
LINEAR-PHASE FIR FILTERS DESIGN Prof. Siripong Potisuk inimum-phase Filters A digital filter is a minimum-phase filter if and only if all of its zeros lie inside or on the unit circle; otherwise, it is
More informationSimple FIR Digital Filters. Simple FIR Digital Filters. Simple Digital Filters. Simple FIR Digital Filters. Simple FIR Digital Filters
Simple Digital Filters Later in the ourse we shall review various methods of designing frequeny-seletive filters satisfying presribed speifiations We now desribe several low-order FIR and IIR digital filters
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 3 Signals & Systems Prof. ark Fowler Note Set #28 D-T Systems: DT Filters Ideal & Practical /4 Ideal D-T Filters Just as in the CT case we can specify filters. We looked at the ideal filter for the
More informationEE 313 Linear Signals & Systems (Fall 2018) Solution Set for Homework #7 on Infinite Impulse Response (IIR) Filters CORRECTED
EE 33 Linear Signals & Systems (Fall 208) Solution Set for Homework #7 on Infinite Impulse Response (IIR) Filters CORRECTED By: Mr. Houshang Salimian and Prof. Brian L. Evans Prolog for the Solution Set.
More informationChapter 7: Filter Design 7.1 Practical Filter Terminology
hapter 7: Filter Design 7. Practical Filter Terminology Analog and digital filters and their designs constitute one of the major emphasis areas in signal processing and communication systems. This is due
More informationFor example, the comb filter generated from. ( ) has a transfer function. e ) has L notches at ω = (2k+1)π/L and L peaks at ω = 2π k/l,
Comb Filers The simple filers discussed so far are characeried eiher by a single passband and/or a single sopband There are applicaions where filers wih muliple passbands and sopbands are required The
More informationECE503: Digital Signal Processing Lecture 5
ECE53: Digital Signal Processing Lecture 5 D. Richard Brown III WPI 3-February-22 WPI D. Richard Brown III 3-February-22 / 32 Lecture 5 Topics. Magnitude and phase characterization of transfer functions
More informationMatched Second Order Digital Filters
Matched Second Order Digital Filters Martin Vicanek 14. February 016 1 Introduction Second order sections are universal building blocks for digital filters. They are characterized by five coefficients,
More informationStability Condition in Terms of the Pole Locations
Stability Condition in Terms of the Pole Locations A causal LTI digital filter is BIBO stable if and only if its impulse response h[n] is absolutely summable, i.e., 1 = S h [ n] < n= We now develop a stability
More informationChapter 7: IIR Filter Design Techniques
IUST-EE Chapter 7: IIR Filter Design Techniques Contents Performance Specifications Pole-Zero Placement Method Impulse Invariant Method Bilinear Transformation Classical Analog Filters DSP-Shokouhi Advantages
More informationELEG 305: Digital Signal Processing
ELEG 305: Digital Signal Processing Lecture : Design of Digital IIR Filters (Part I) Kenneth E. Barner Department of Electrical and Computer Engineering University of Delaware Fall 008 K. E. Barner (Univ.
More informationDigital Filter Structures
Digital Filter Structures Te convolution sum description of an LTI discrete-time system can, in principle, be used to implement te system For an IIR finite-dimensional system tis approac is not practical
More informationBasic Design Approaches
(Classic) IIR filter design: Basic Design Approaches. Convert the digital filter specifications into an analog prototype lowpass filter specifications. Determine the analog lowpass filter transfer function
More informationFILTER DESIGN FOR SIGNAL PROCESSING USING MATLAB AND MATHEMATICAL
FILTER DESIGN FOR SIGNAL PROCESSING USING MATLAB AND MATHEMATICAL Miroslav D. Lutovac The University of Belgrade Belgrade, Yugoslavia Dejan V. Tosic The University of Belgrade Belgrade, Yugoslavia Brian
More informationDeliyannis, Theodore L. et al "Two Integrator Loop OTA-C Filters" Continuous-Time Active Filter Design Boca Raton: CRC Press LLC,1999
Deliyannis, Theodore L. et al "Two Integrator Loop OTA-C Filters" Continuous-Time Active Filter Design Boca Raton: CRC Press LLC,1999 Chapter 9 Two Integrator Loop OTA-C Filters 9.1 Introduction As discussed
More informationMULTIRATE SYSTEMS. work load, lower filter order, lower coefficient sensitivity and noise,
MULIRAE SYSEMS ransfer signals between two systems that operate with different sample frequencies Implemented system functions more efficiently by using several sample rates (for example narrow-band filters).
More informationHow to manipulate Frequencies in Discrete-time Domain? Two Main Approaches
How to manipulate Frequencies in Discrete-time Domain? Two Main Approaches Difference Equations (an LTI system) x[n]: input, y[n]: output That is, building a system that maes use of the current and previous
More informationMultirate Digital Signal Processing
Multirate Digital Signal Processing Basic Sampling Rate Alteration Devices Up-sampler - Used to increase the sampling rate by an integer factor Down-sampler - Used to decrease the sampling rate by an integer
More informationLTI Discrete-Time Systems in Transform Domain Ideal Filters Zero Phase Transfer Functions Linear Phase Transfer Functions
LTI Discrete-Time Systems in Transform Domain Ideal Filters Zero Pase Transfer Functions Linear Pase Transfer Functions Tania Stataki 811b t.stataki@imperial.ac.uk Types of Transfer Functions Te time-domain
More informationEE482: Digital Signal Processing Applications
Professor Brendan Morris, SEB 3216, brendan.morris@unlv.edu EE482: Digital Signal Processing Applications Spring 2014 TTh 14:30-15:45 CBC C222 Lecture 05 IIR Design 14/03/04 http://www.ee.unlv.edu/~b1morris/ee482/
More informationElectronic Circuits EE359A
Electronic Circuits EE359A Bruce McNair B26 bmcnair@stevens.edu 21-216-5549 Lecture 22 578 Second order LCR resonator-poles V o I 1 1 = = Y 1 1 + sc + sl R s = C 2 s 1 s + + CR LC s = C 2 sω 2 s + + ω
More informationExperiment 13 Poles and zeros in the z plane: IIR systems
Experiment 13 Poles and zeros in the z plane: IIR systems Achievements in this experiment You will be able to interpret the poles and zeros of the transfer function of discrete-time filters to visualize
More informationSecond-order filters. EE 230 second-order filters 1
Second-order filters Second order filters: Have second order polynomials in the denominator of the transfer function, and can have zeroth-, first-, or second-order polynomials in the numerator. Use two
More informationComputer-Aided Design of Digital Filters. Digital Filters. Digital Filters. Digital Filters. Design of Equiripple Linear-Phase FIR Filters
Computer-Aided Design of Digital Filters The FIR filter design techniques discussed so far can be easily implemented on a computer In addition, there are a number of FIR filter design algorithms that rely
More informationDesign of Narrow Stopband Recursive Digital Filter
FACTA UNIVERSITATIS (NIŠ) SER.: ELEC. ENERG. vol. 24, no. 1, April 211, 119-13 Design of Narrow Stopband Recursive Digital Filter Goran Stančić and Saša Nikolić Abstract: The procedure for design of narrow
More informationLecture 7 - IIR Filters
Lecture 7 - IIR Filters James Barnes (James.Barnes@colostate.edu) Spring 204 Colorado State University Dept of Electrical and Computer Engineering ECE423 / 2 Outline. IIR Filter Representations Difference
More informationDigital Signal Processing
COMP ENG 4TL4: Digital Signal Processing Notes for Lecture #21 Friday, October 24, 2003 Types of causal FIR (generalized) linear-phase filters: Type I: Symmetric impulse response: with order M an even
More informationLecture 19 IIR Filters
Lecture 19 IIR Filters Fundamentals of Digital Signal Processing Spring, 2012 Wei-Ta Chu 2012/5/10 1 General IIR Difference Equation IIR system: infinite-impulse response system The most general class
More informationThe basic structure of the L-channel QMF bank is shown below
-Channel QMF Bans The basic structure of the -channel QMF ban is shown below The expressions for the -transforms of various intermediate signals in the above structure are given by Copyright, S. K. Mitra
More informationSYNTHESIS OF BIRECIPROCAL WAVE DIGITAL FILTERS WITH EQUIRIPPLE AMPLITUDE AND PHASE
SYNTHESIS OF BIRECIPROCAL WAVE DIGITAL FILTERS WITH EQUIRIPPLE AMPLITUDE AND PHASE M. Yaseen Dept. of Electrical and Electronic Eng., University of Assiut Assiut, Egypt Tel: 088-336488 Fax: 088-33553 E-Mail
More informationELEG 305: Digital Signal Processing
ELEG 305: Digital Signal Processing Lecture 19: Lattice Filters Kenneth E. Barner Department of Electrical and Computer Engineering University of Delaware Fall 2008 K. E. Barner (Univ. of Delaware) ELEG
More informationELEG 5173L Digital Signal Processing Ch. 5 Digital Filters
Department of Electrical Engineering University of Aransas ELEG 573L Digital Signal Processing Ch. 5 Digital Filters Dr. Jingxian Wu wuj@uar.edu OUTLINE 2 FIR and IIR Filters Filter Structures Analog Filters
More informationDiscrete-time first-order systems
Discrete-time first-order systems 1 Start with the continuous-time system ẏ(t) =ay(t)+bu(t), y(0) Zero-order hold input u(t) =u(nt ), nt apple t
More informationPS403 - Digital Signal processing
PS403 - Digital Signal processing 6. DSP - Recursive (IIR) Digital Filters Key Text: Digital Signal Processing with Computer Applications (2 nd Ed.) Paul A Lynn and Wolfgang Fuerst, (Publisher: John Wiley
More informationDESIGN OF LINEAR-PHASE LATTICE WAVE DIGITAL FILTERS
DESIGN OF LINEAR-PHASE LAICE WAVE DIGIAL FILERS HŒkan Johansson and Lars Wanhammar Department of Electrical Engineering, Linkšping University S-58 83 Linkšping, Sweden E-mail: hakanj@isy.liu.se, larsw@isy.liu.se
More informationEE 508 Lecture 15. Filter Transformations. Lowpass to Bandpass Lowpass to Highpass Lowpass to Band-reject
EE 508 Lecture 15 Filter Transformations Lowpass to Bandpass Lowpass to Highpass Lowpass to Band-reject Review from Last Time Thompson and Bessel pproximations Use of Bessel Filters: X I (s) X OUT (s)
More informationAnalog and Digital Filter Design
Analog and Digital Filter Design by Jens Hee http://jenshee.dk October 208 Change log 28. september 208. Document started.. october 208. Figures added. 6. october 208. Bilinear transform chapter extended.
More informationDIGITAL SIGNAL PROCESSING UNIT III INFINITE IMPULSE RESPONSE DIGITAL FILTERS. 3.6 Design of Digital Filter using Digital to Digital
DIGITAL SIGNAL PROCESSING UNIT III INFINITE IMPULSE RESPONSE DIGITAL FILTERS Contents: 3.1 Introduction IIR Filters 3.2 Transformation Function Derivation 3.3 Review of Analog IIR Filters 3.3.1 Butterworth
More informationAnalysis of Finite Wordlength Effects
Analysis of Finite Wordlength Effects Ideally, the system parameters along with the signal variables have infinite precision taing any value between and In practice, they can tae only discrete values within
More informationLectures on APPLICATIONS
APP0 University of alifornia Berkeley ollege of Engineering Department of Electrical Engineering and omputer Science obert W. Brodersen EES40 Analog ircuit Design t ISE Lectures on APPLIATINS t FALL.0V
More informationTransform analysis of LTI systems Oppenheim and Schafer, Second edition pp For LTI systems we can write
Transform analysis of LTI systems Oppenheim and Schafer, Second edition pp. 4 9. For LTI systems we can write yœn D xœn hœn D X kd xœkhœn Alternatively, this relationship can be expressed in the z-transform
More informationDISCRETE-TIME SIGNAL PROCESSING
THIRD EDITION DISCRETE-TIME SIGNAL PROCESSING ALAN V. OPPENHEIM MASSACHUSETTS INSTITUTE OF TECHNOLOGY RONALD W. SCHÄFER HEWLETT-PACKARD LABORATORIES Upper Saddle River Boston Columbus San Francisco New
More informationComputer Engineering 4TL4: Digital Signal Processing
Computer Engineering 4TL4: Digital Signal Processing Day Class Instructor: Dr. I. C. BRUCE Duration of Examination: 3 Hours McMaster University Final Examination December, 2003 This examination paper includes
More informationOversampling Converters
Oversampling Converters David Johns and Ken Martin (johns@eecg.toronto.edu) (martin@eecg.toronto.edu) slide 1 of 56 Motivation Popular approach for medium-to-low speed A/D and D/A applications requiring
More informationUNIT - III PART A. 2. Mention any two techniques for digitizing the transfer function of an analog filter?
UNIT - III PART A. Mention the important features of the IIR filters? i) The physically realizable IIR filters does not have linear phase. ii) The IIR filter specification includes the desired characteristics
More informationEfficient 2D Linear-Phase IIR Filter Design and Application in Image Filtering
Efficient D Linear-Phase IIR Filter Design and Application in Image Filtering Chi-Un Lei, Chung-Man Cheung, and Ngai Wong Abstract We present an efficient and novel procedure to design two-dimensional
More informationFilter Analysis and Design
Filter Analysis and Design Butterworth Filters Butterworth filters have a transfer function whose squared magnitude has the form H a ( jω ) 2 = 1 ( ) 2n. 1+ ω / ω c * M. J. Roberts - All Rights Reserved
More informationElectronic Circuits EE359A
Electronic Circuits EE359A Bruce McNair B26 bmcnair@stevens.edu 21-216-5549 Lecture 22 569 Second order section Ts () = s as + as+ a 2 2 1 ω + s+ ω Q 2 2 ω 1 p, p = ± 1 Q 4 Q 1 2 2 57 Second order section
More informationLinear Convolution Using FFT
Linear Convolution Using FFT Another useful property is that we can perform circular convolution and see how many points remain the same as those of linear convolution. When P < L and an L-point circular
More informationContinuous and Discrete Time Signals and Systems
Continuous and Discrete Time Signals and Systems Mrinal Mandal University of Alberta, Edmonton, Canada and Amir Asif York University, Toronto, Canada CAMBRIDGE UNIVERSITY PRESS Contents Preface Parti Introduction
More informationECE 410 DIGITAL SIGNAL PROCESSING D. Munson University of Illinois Chapter 12
. ECE 40 DIGITAL SIGNAL PROCESSING D. Munson University of Illinois Chapter IIR Filter Design ) Based on Analog Prototype a) Impulse invariant design b) Bilinear transformation ( ) ~ widely used ) Computer-Aided
More informationImplementation of Discrete-Time Systems
EEE443 Digital Signal Processing Implementation of Discrete-Time Systems Dr. Shahrel A. Suandi PPKEE, Engineering Campus, USM Introduction A linear-time invariant system (LTI) is described by linear constant
More information# FIR. [ ] = b k. # [ ]x[ n " k] [ ] = h k. x[ n] = Ae j" e j# ˆ n Complex exponential input. [ ]Ae j" e j ˆ. ˆ )Ae j# e j ˆ. y n. y n.
[ ] = h k M [ ] = b k x[ n " k] FIR k= M [ ]x[ n " k] convolution k= x[ n] = Ae j" e j ˆ n Complex exponential input [ ] = h k M % k= [ ]Ae j" e j ˆ % M = ' h[ k]e " j ˆ & k= k = H (" ˆ )Ae j e j ˆ ( )
More informationAll-Pole Recursive Digital Filters Design Based on Ultraspherical Polynomials
RADIOENGINEERING, VOL. 3, NO. 3, SEPTEMBER 4 949 All-Pole Recursive Digital Filters Design Based on Ultraspherical Polynomials Nikola STOJANOVIĆ, Negovan STAMENKOVIĆ, Vidosav STOJANOVIĆ University of Niš,
More informationFilter Design Problem
Filter Design Problem Design of frequency-selective filters usually starts with a specification of their frequency response function. Practical filters have passband and stopband ripples, while exhibiting
More informationZ - Transform. It offers the techniques for digital filter design and frequency analysis of digital signals.
Z - Transform The z-transform is a very important tool in describing and analyzing digital systems. It offers the techniques for digital filter design and frequency analysis of digital signals. Definition
More informationFilter structures ELEC-E5410
Filter structures ELEC-E5410 Contents FIR filter basics Ideal impulse responses Polyphase decomposition Fractional delay by polyphase structure Nyquist filters Half-band filters Gibbs phenomenon Discrete-time
More informationMultidimensional digital signal processing
PSfrag replacements Two-dimensional discrete signals N 1 A 2-D discrete signal (also N called a sequence or array) is a function 2 defined over thex(n set 1 of, n 2 ordered ) pairs of integers: y(nx 1,
More informationRecursive, Infinite Impulse Response (IIR) Digital Filters:
Recursive, Infinite Impulse Response (IIR) Digital Filters: Filters defined by Laplace Domain transfer functions (analog devices) can be easily converted to Z domain transfer functions (digital, sampled
More informationCMPT 889: Lecture 5 Filters
CMPT 889: Lecture 5 Filters Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University October 7, 2009 1 Digital Filters Any medium through which a signal passes may be regarded
More informationDigital Filters. Linearity and Time Invariance. Linear Time-Invariant (LTI) Filters: CMPT 889: Lecture 5 Filters
Digital Filters CMPT 889: Lecture 5 Filters Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University October 7, 29 Any medium through which a signal passes may be regarded as
More information1. FIR Filter Design
ELEN E4810: Digital Signal Processing Topic 9: Filter Design: FIR 1. Windowed Impulse Response 2. Window Shapes 3. Design by Iterative Optimization 1 1. FIR Filter Design! FIR filters! no poles (just zeros)!
More informationDSP Configurations. responded with: thus the system function for this filter would be
DSP Configurations In this lecture we discuss the different physical (or software) configurations that can be used to actually realize or implement DSP functions. Recall that the general form of a DSP
More informationFrequency Response of Discrete-Time Systems
Frequency Response of Discrete-Time Systems EE 37 Signals and Systems David W. Graham 6 Relationship of Pole-Zero Plot to Frequency Response Zeros Roots of the numerator Pin the system to a value of ero
More informationEFFICIENT REMEZ ALGORITHMS FOR THE DESIGN OF NONRECURSIVE FILTERS
EFFICIENT REMEZ ALGORITHMS FOR THE DESIGN OF NONRECURSIVE FILTERS Copyright 2003- Andreas Antoniou Victoria, BC, Canada Email: aantoniou@ieee.org July 24, 2007 Frame # 1 Slide # 1 A. Antoniou EFFICIENT
More informationDesign of Biorthogonal FIR Linear Phase Filter Banks with Structurally Perfect Reconstruction
Electronics and Communications in Japan, Part 3, Vol. 82, No. 1, 1999 Translated from Denshi Joho Tsushin Gakkai Ronbunshi, Vol. J81-A, No. 1, January 1998, pp. 17 23 Design of Biorthogonal FIR Linear
More informationModule 4 MULTI- RESOLUTION ANALYSIS. Version 2 ECE IIT, Kharagpur
Module MULTI- RESOLUTION ANALYSIS Version ECE IIT, Kharagpur Lesson Multi-resolution Analysis: Theory of Subband Coding Version ECE IIT, Kharagpur Instructional Objectives At the end of this lesson, the
More informationNEW STEIGLITZ-McBRIDE ADAPTIVE LATTICE NOTCH FILTERS
NEW STEIGLITZ-McBRIDE ADAPTIVE LATTICE NOTCH FILTERS J.E. COUSSEAU, J.P. SCOPPA and P.D. DOÑATE CONICET- Departamento de Ingeniería Eléctrica y Computadoras Universidad Nacional del Sur Av. Alem 253, 8000
More information1 1.27z z 2. 1 z H 2
E481 Digital Signal Processing Exam Date: Thursday -1-1 16:15 18:45 Final Exam - Solutions Dan Ellis 1. (a) In this direct-form II second-order-section filter, the first stage has
More informationToday. ESE 531: Digital Signal Processing. IIR Filter Design. Impulse Invariance. Impulse Invariance. Impulse Invariance. ω < π.
Today ESE 53: Digital Signal Processing! IIR Filter Design " Lec 8: March 30, 207 IIR Filters and Adaptive Filters " Bilinear Transformation! Transformation of DT Filters! Adaptive Filters! LMS Algorithm
More informationbutter butter Purpose Syntax Description Digital Domain Analog Domain
butter butter 7butter Butterworth analog and digital filter design [b,a] = butter(n,wn) [b,a] = butter(n,wn,'ftype') [b,a] = butter(n,wn,'s') [b,a] = butter(n,wn,'ftype','s') [z,p,k] = butter(...) [A,B,C,D]
More informationTransform Analysis of Linear Time-Invariant Systems
Transform Analysis of Linear Time-Invariant Systems Discrete-Time Signal Processing Chia-Ping Chen Department of Computer Science and Engineering National Sun Yat-Sen University Kaohsiung, Taiwan ROC Transform
More informationOn the Frequency-Domain Properties of Savitzky-Golay Filters
On the Frequency-Domain Properties of Savitzky-Golay Filters Ronald W Schafer HP Laboratories HPL-2-9 Keyword(s): Savitzky-Golay filter, least-squares polynomial approximation, smoothing Abstract: This
More informationReview Problems 3. Four FIR Filter Types
Review Prblems 3 Fur FIR Filter Types Fur types f FIR linear phase digital filters have cefficients h(n fr 0 n M. They are defined as fllws: Type I: h(n = h(m-n and M even. Type II: h(n = h(m-n and M dd.
More informationECE4270 Fundamentals of DSP Lecture 20. Fixed-Point Arithmetic in FIR and IIR Filters (part I) Overview of Lecture. Overflow. FIR Digital Filter
ECE4270 Fundamentals of DSP Lecture 20 Fixed-Point Arithmetic in FIR and IIR Filters (part I) School of ECE Center for Signal and Information Processing Georgia Institute of Technology Overview of Lecture
More informationFourier Series Representation of
Fourier Series Representation of Periodic Signals Rui Wang, Assistant professor Dept. of Information and Communication Tongji University it Email: ruiwang@tongji.edu.cn Outline The response of LIT system
More informationExercises in Digital Signal Processing
Exercises in Digital Signal Processing Ivan W. Selesnick September, 5 Contents The Discrete Fourier Transform The Fast Fourier Transform 8 3 Filters and Review 4 Linear-Phase FIR Digital Filters 5 5 Windows
More informationAPPLIED SIGNAL PROCESSING
APPLIED SIGNAL PROCESSING DIGITAL FILTERS Digital filters are discrete-time linear systems { x[n] } G { y[n] } Impulse response: y[n] = h[0]x[n] + h[1]x[n 1] + 2 DIGITAL FILTER TYPES FIR (Finite Impulse
More informationOther types of errors due to using a finite no. of bits: Round- off error due to rounding of products
ECE 8440 Unit 12 More on finite precision representa.ons (See sec.on 6.7) Already covered: quan.za.on error due to conver.ng an analog signal to a digital signal. 1 Other types of errors due to using a
More informationTopic 7: Filter types and structures
ELEN E481: Digital Signal Processing Topic 7: Filter tpes and structures 1. Some filter tpes 2. Minimum and maximum phase 3. Filter implementation structures 1 1. Some Filter Tpes We have seen the basics
More informationThe Discrete-Time Fourier
Chapter 3 The Discrete-Time Fourier Transform 清大電機系林嘉文 cwlin@ee.nthu.edu.tw 03-5731152 Original PowerPoint slides prepared by S. K. Mitra 3-1-1 Continuous-Time Fourier Transform Definition The CTFT of
More informationDesign of Narrow Band Filters Part 2
E.U.I.T. Telecomunicación 200, Madrid, Spain, 27.09 30.09.200 Design of Narrow Band Filters Part 2 Thomas Buch Institute of Communications Engineering University of Rostock Th. Buch, Institute of Communications
More informationDSP. Chapter-3 : Filter Design. Marc Moonen. Dept. E.E./ESAT-STADIUS, KU Leuven
DSP Chapter-3 : Filter Design Marc Moonen Dept. E.E./ESAT-STADIUS, KU Leuven marc.moonen@esat.kuleuven.be www.esat.kuleuven.be/stadius/ Filter Design Process Step-1 : Define filter specs Pass-band, stop-band,
More informationMultimedia Signals and Systems - Audio and Video. Signal, Image, Video Processing Review-Introduction, MP3 and MPEG2
Multimedia Signals and Systems - Audio and Video Signal, Image, Video Processing Review-Introduction, MP3 and MPEG2 Kunio Takaya Electrical and Computer Engineering University of Saskatchewan December
More informationEE538 Final Exam Fall 2007 Mon, Dec 10, 8-10 am RHPH 127 Dec. 10, Cover Sheet
EE538 Final Exam Fall 2007 Mon, Dec 10, 8-10 am RHPH 127 Dec. 10, 2007 Cover Sheet Test Duration: 120 minutes. Open Book but Closed Notes. Calculators allowed!! This test contains five problems. Each of
More information