IIR Filter Design Chapter Intended Learning Outcomes: (i) Ability to design analog Butterworth filters

Similar documents
(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters

(i) Understanding of the characteristics of linear-phase finite impulse response (FIR) filters

Analog Lowpass Filter Specifications

Chapter 7 Filter Design Techniques. Filter Design Techniques

EE 470 Signals and Systems

NH 67, Karur Trichy Highways, Puliyur C.F, Karur District DEPARTMENT OF INFORMATION TECHNOLOGY DIGITAL SIGNAL PROCESSING UNIT 3

Infinite Impulse Response (IIR) Filter. Ikhwannul Kholis, ST., MT. Universitas 17 Agustus 1945 Jakarta

Digital Signal Processing

ELEC-C5230 Digitaalisen signaalinkäsittelyn perusteet

4. Design of Discrete-Time Filters

Digital Processing of Continuous-Time Signals

Digital Processing of

DIGITAL FILTERS. !! Finite Impulse Response (FIR) !! Infinite Impulse Response (IIR) !! Background. !! Matlab functions AGC DSP AGC DSP

Part B. Simple Digital Filters. 1. Simple FIR Digital Filters

UNIT II IIR FILTER DESIGN

Copyright S. K. Mitra

ECE503: Digital Filter Design Lecture 9

8: IIR Filter Transformations

LECTURER NOTE SMJE3163 DSP


1 PeZ: Introduction. 1.1 Controls for PeZ using pezdemo. Lab 15b: FIR Filter Design and PeZ: The z, n, and O! Domains

Multirate Digital Signal Processing

Team proposals are due tomorrow at 6PM Homework 4 is due next thur. Proposal presentations are next mon in 1311EECS.

The University of Texas at Austin Dept. of Electrical and Computer Engineering Midterm #2

Digital Filtering: Realization

GEORGIA INSTITUTE OF TECHNOLOGY. SCHOOL of ELECTRICAL and COMPUTER ENGINEERING. ECE 2026 Summer 2018 Lab #8: Filter Design of FIR Filters

DESIGN OF FIR AND IIR FILTERS

Design of infinite impulse response (IIR) bandpass filter structure using particle swarm optimization

Review of Filter Types

ECE438 - Laboratory 7a: Digital Filter Design (Week 1) By Prof. Charles Bouman and Prof. Mireille Boutin Fall 2015

EEM478-DSPHARDWARE. WEEK12:FIR & IIR Filter Design

F I R Filter (Finite Impulse Response)

Design IIR Filter using MATLAB

Advanced Digital Signal Processing Part 5: Digital Filters

Filters. Phani Chavali

NOVEMBER 13, 1996 EE 4773/6773: LECTURE NO. 37 PAGE 1 of 5

EEO 401 Digital Signal Processing Prof. Mark Fowler

Brief Introduction to Signals & Systems. Phani Chavali

UNIT-II MYcsvtu Notes agk

Discretization of Continuous Controllers

EELE 4310: Digital Signal Processing (DSP)

ECE 203 LAB 2 PRACTICAL FILTER DESIGN & IMPLEMENTATION

Digital Filters IIR (& Their Corresponding Analog Filters) Week Date Lecture Title

ECE 429 / 529 Digital Signal Processing

Sampling and Reconstruction of Analog Signals

Digital Filters IIR (& Their Corresponding Analog Filters) 4 April 2017 ELEC 3004: Systems 1. Week Date Lecture Title

Final Exam. EE313 Signals and Systems. Fall 1999, Prof. Brian L. Evans, Unique No

Window Method. designates the window function. Commonly used window functions in FIR filters. are: 1. Rectangular Window:

Continuous-Time Analog Filters

SMS045 - DSP Systems in Practice. Lab 1 - Filter Design and Evaluation in MATLAB Due date: Thursday Nov 13, 2003

The University of Texas at Austin Dept. of Electrical and Computer Engineering Final Exam

Digital Signal Processing

ELEC3104: Digital Signal Processing Session 1, 2013

Experiment 4- Finite Impulse Response Filters

EC6502 PRINCIPLES OF DIGITAL SIGNAL PROCESSING

3 Analog filters. 3.1 Analog filter characteristics

Design of IIR Digital Filters with Flat Passband and Equiripple Stopband Responses

EEL 3923C. JD/ Module 3 Elementary Analog Filter Design. Prof. T. Nishida Fall 2010

Filters and Tuned Amplifiers

(Refer Slide Time: 02:00-04:20) (Refer Slide Time: 04:27 09:06)

Designing Filters Using the NI LabVIEW Digital Filter Design Toolkit

Frequency-Response Masking FIR Filters

DSP Laboratory (EELE 4110) Lab#10 Finite Impulse Response (FIR) Filters

ECE 4213/5213 Homework 10

Problem Point Value Your score Topic 1 28 Filter Analysis 2 24 Filter Implementation 3 24 Filter Design 4 24 Potpourri Total 100

Design of FIR Filters

4/14/15 8:58 PM C:\Users\Harrn...\tlh2polebutter10rad see.rn 1 of 1

Signal processing preliminaries

APPENDIX A to VOLUME A1 TIMS FILTER RESPONSES

Massachusetts Institute of Technology Department of Electrical Engineering & Computer Science 6.341: Discrete-Time Signal Processing Fall 2005

Digital Filter Design

EE 422G - Signals and Systems Laboratory

Signals and Systems Lecture 6: Fourier Applications

B.Tech III Year II Semester (R13) Regular & Supplementary Examinations May/June 2017 DIGITAL SIGNAL PROCESSING (Common to ECE and EIE)

Plot frequency response around the unit circle above the Z-plane.

Noise removal example. Today s topic. Digital Signal Processing. Lecture 3. Application Specific Integrated Circuits for

ijdsp Workshop: Exercise 2012 DSP Exercise Objectives

Module 3 : Sampling and Reconstruction Problem Set 3

Classic Filters. Figure 1 Butterworth Filter. Chebyshev

(i) Understanding the basic concepts of signal modeling, correlation, maximum likelihood estimation, least squares and iterative numerical methods

Narrow-Band Low-Pass Digital Differentiator Design. Ivan Selesnick Polytechnic University Brooklyn, New York

ASN Filter Designer Professional/Lite Getting Started Guide

APPLIED SIGNAL PROCESSING

Analog Design-filters

Advanced Digital Signal Processing Part 2: Digital Processing of Continuous-Time Signals

Spectral Transformation On the unit circle we have

CS3291: Digital Signal Processing

Chapter 2 Infinite Impulse Response (IIR) Filter

Octave Functions for Filters. Young Won Lim 2/19/18

Digital Filters FIR and IIR Systems

Bandpass Filters Using Capacitively Coupled Series Resonators

E Final Exam Solutions page 1/ gain / db Imaginary Part

Signals and Systems Lecture 6: Fourier Applications

EEM478-WEEK8 Finite Impulse Response (FIR) Filters

PHYS225 Lecture 15. Electronic Circuits

Interpolated Lowpass FIR Filters

Computer-Aided Design (CAD) of Recursive/Non-Recursive Filters

2.1 BASIC CONCEPTS Basic Operations on Signals Time Shifting. Figure 2.2 Time shifting of a signal. Time Reversal.

Rahman Jamal, et. al.. "Filters." Copyright 2000 CRC Press LLC. <

EE 230 Lecture 39. Data Converters. Time and Amplitude Quantization

Transcription:

IIR Filter Design Chapter Intended Learning Outcomes: (i) Ability to design analog Butterworth filters (ii) Ability to design lowpass IIR filters according to predefined specifications based on analog filter theory and analog-to-digital filter transformation (iii) Ability to construct frequency-selective IIR filters based on a lowpass IIR filter H. C. So Page 1 Semester A 2017-2018

Steps in Infinite Impulse Response Filter Design The system transfer function of an IIR filter is: (11.1) The task in IIR filter design is to find and such that satisfies the given specifications. Once is computed, the filter can then be realized in hardware or software according to a direct, canonic, cascade or parallel form H. C. So Page 2 Semester A 2017-2018

We make use of the analog filter design to produce the required filter specifications analog lowpass filter design analog-to-digital filter transformation frequency band transformation Fig.11.1: Steps in determining transfer function of IIR filter Note that is the Laplace transform parameter and substituting in yields the Fourier transform of the filter, that is, Main drawback is that there is no control over the phase response of, implying that the filter requirements can only be specified in terms of magnitude response H. C. So Page 3 Semester A 2017-2018

Butterworth Lowpass Filter Design In analog lowpass filter design, we can only specify the magnitude of. Typically, we employ the magnitude square response, that is, : passband transition stopband Fig.11.2: Specifications of analog lowpass filter H. C. So Page 4 Semester A 2017-2018

Passband corresponds to where is the passband frequency and is called the passband ripple Stopband corresponds to where is the stopband frequency and is called the stopband attenuation Transition band corresponds to The specifications are represented as the two inequalities: (11.2) and (11.3) H. C. So Page 5 Semester A 2017-2018

In particular, at and, we have: (11.4) and (11.5) Apart from and, it is also common to use their respective db versions, denoted by and : (11.6) and (11.7) H. C. So Page 6 Semester A 2017-2018

The magnitude square response of a lowpass filter is: th-order Butterworth (11.8) The filter is characterized by and, which represent the cutoff frequency and filter order at and at for all is a monotonically decreasing function of frequency which indicates that there is no ripple filter shape is closer to the ideal response as increases, although the filter with order of is not realizable. H. C. So Page 7 Semester A 2017-2018

Fig.11.3: Magnitude square responses of Butterworth lowpass filter H. C. So Page 8 Semester A 2017-2018

To determine :, we first make use of its relationship with (11.9) From (11.8)-(11.9), we obtain: (11.10) The poles of, denoted by,, are given as: (11.11) H. C. So Page 9 Semester A 2017-2018

-plane -plane Fig.11.4: Poles of Butterworth lowpass filter H. C. So Page 10 Semester A 2017-2018

are uniformly distributed on a circle of radius with angular spacing of in the -plane poles are symmetrically located with respect to the imaginary axis there are two real-valued poles when is odd To extract from (11.10), we utilize the knowledge that all poles of a stable and causal analog filter should be on the left half of the -plane. As a result, is: (11.12) H. C. So Page 11 Semester A 2017-2018

Example 11.1 The magnitude square response of a Butterworth lowpass filter has the form of: Determine the filter transfer function. Expressing as: From (11.8), and H. C. So Page 12 Semester A 2017-2018

From (11.11): Finally, we apply (11.12) to obtain: H. C. So Page 13 Semester A 2017-2018

To find and given the passband and stopband requirements in terms of,, and, we exploit (11.4)-(11.5) together with (11.6)-(11.7) to obtain (11.13) and (11.14) H. C. So Page 14 Semester A 2017-2018

Solving (11.13)-(11.14) and noting that integer, we get should be an (11.15) where rounds up to the nearest integer. The is then obtained from (11.13) or (11.14) so that the specification can be exactly met at or, respectively From (11.13), is computed as: (11.16) H. C. So Page 15 Semester A 2017-2018

From (11.14), is computed as: (11.17) As a result, the admissible range of is: (11.18) Example 11.2 Determine the transfer function of a Butterworth lowpass filter whose magnitude requirements are,, db and db. H. C. So Page 16 Semester A 2017-2018

Employing (11.15) yields: Putting in (11.18), the cutoff frequency is: For simplicity, we select filter transfer function is:. Using Example 11.1, the H. C. So Page 17 Semester A 2017-2018

0 Magnitude Square Response -8-16 -50 0 4 6 20 Ω/p Fig.11.5: Magnitude square response of Butterworth lowpass filter H. C. So Page 18 Semester A 2017-2018

The MATLAB program is provided as ex11_2.m where the command freqs, which is analogous to freqz, is used to plot Analog-to-Digital Filter Transformation Typical methods include impulse invariance, bilinear transformation, backward difference approximation and matched- transformation Their common feature is that a stable analog filter will transform to a stable system with transfer function. Left half of -plane maps into inside of unit circle in -plane Each has its pros and cons and thus optimal transformation does not exist H. C. So Page 19 Semester A 2017-2018

Impulse Invariance The idea is simply to sample impulse response of the analog filter to obtain the digital lowpass filter impulse response The relationship between and is (11.19) where is the sampling interval Why there is a scaling of T? H. C. So Page 20 Semester A 2017-2018

With the use of (4.5) and (5.3)-(5.4), is: (11.20) where the analog and digital frequencies are related as: (11.21) The impulse response of the resultant IIR filter is similar to that of the analog filter Aliasing due to the overlapping of which are not bandlimited. However, corresponds to a lowpass filter and thus aliasing effect is negligibly small. H. C. So Page 21 Semester A 2017-2018

To derive the IIR filter transfer function from, we first obtain the partial fraction expansion: (11.22) where are the poles on the left half of the -plane The inverse Laplace transform of (11.22) is given as: (11.23) H. C. So Page 22 Semester A 2017-2018

Substituting (11.23) into (11.19), we have: (11.24) The transform of is: (11.25) Comparing (11.22) and (11.25), it is seen that a pole of in the -plane transforms to a pole at in the - plane: (11.26) H. C. So Page 23 Semester A 2017-2018

Expressing : (11.27) where is any integer, indicating a many-to-one mapping Each infinite horizontal strip of width entire -plane maps into the maps to, that is, axis in the -plane transforms to the unit circle in the -plane maps to, stable produces stable maps to, right half of the -plane maps into the outside of the unit circle in the -plane H. C. So Page 24 Semester A 2017-2018

-plane -plane Fig.11.6: Mapping between and in impulse invariance method H. C. So Page 25 Semester A 2017-2018

Given the magnitude square response specifications of in terms of,, and, the design procedure for based on the impulse invariance method is summarized as the following steps: (i) Select a value for the sampling interval and then compute the passband and stopband frequencies for the analog lowpass filter according to and (ii) Design the analog Butterworth filter with transfer function according to,, and (iii)perform partial fraction expansion on as in (11.22) (iv)obtain using (11.25) H. C. So Page 26 Semester A 2017-2018

Example 11.3 The transfer function of an analog filter has the form of Use impulse invariance method with sampling interval to transform to a digital filter transfer function. Performing partial fraction expansion on : Applying (11.25) with yields H. C. So Page 27 Semester A 2017-2018

Example 11.4 Determine the transfer function of a digital lowpass filter whose magnitude requirements are,, db and db. Use the Butterworth lowpass filter and impulse invariance method in the design. Selecting the sampling interval as frequency parameters are computed as:, the analog and H. C. So Page 28 Semester A 2017-2018

Using Example 11.2, a Butterworth filter which meets the magnitude requirements are: Performing partial fraction expansion on of the MATLAB command residue, we get with the use Applying (11.25) with yields H. C. So Page 29 Semester A 2017-2018

The MATLAB program is provided as ex11_4.m. H. C. So Page 30 Semester A 2017-2018

0 Magnitude (db) -8-16 -30 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) 0 Phase (degrees) -100-200 -300 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) Fig.11.7: Magnitude and phase responses based on impulse invariance H. C. So Page 31 Semester A 2017-2018

Bilinear Transformation It is a conformal mapping that maps the axis of the - plane into the unit circle of the -plane only once, implying there is no aliasing problem as in the impulse invariance method It is a one-to-one mapping The relationship between and is: (11.28) H. C. So Page 32 Semester A 2017-2018

Employing, can be expressed as: (11.29) maps to, that is, axis in the -plane transforms to the unit circle in the -plane maps to, stable produces a stable maps to, right half of the -plane maps into the outside of the unit circle in the -plane H. C. So Page 33 Semester A 2017-2018

-plane -plane Fig.11.8: Mapping between and in bilinear transformation H. C. So Page 34 Semester A 2017-2018

Although aliasing is avoided, the drawback of the bilinear transformation is that there is no linear relationship between and Putting and in (11.28), and are related as: (11.30) Given the magnitude square response specifications of in terms of,, and, the design procedure for based on the bilinear transformation is summarized as the following steps: H. C. So Page 35 Semester A 2017-2018

(i) Select a value for and then compute the passband and stopband frequencies for the analog lowpass filter according and (ii) Design the analog Butterworth filter with transfer function according to,, and. (iii)obtain from using the substitution of (11.28). Example 11.5 The transfer function of an analog filter has the form of Use the bilinear transformation with to transform to a digital filter with transfer function. H. C. So Page 36 Semester A 2017-2018

Applying (11.28) with yields Example 11.6 Determine the transfer function of a digital lowpass filter whose magnitude requirements are,, db and db. Use the Butterworth lowpass filter and bilinear transformation in the design. Selecting, the analog frequency parameters are computed according to (11.30) as: H. C. So Page 37 Semester A 2017-2018

and Employing (11.15) yields: Putting in (11.18), the cutoff frequency is: H. C. So Page 38 Semester A 2017-2018

For simplicity, is employed. Following (11.11)-(11.12): Finally, we use (11.28) with to yield The MATLAB program is provided as ex11_6.m. H. C. So Page 39 Semester A 2017-2018

0 Magnitude (db) -8-16 -30 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) 0 Phase (degrees) -50-100 -150-200 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) Fig.11.9: Magnitude and phase responses based on bilinear transformation H. C. So Page 40 Semester A 2017-2018

Frequency Band Transformation The operations are similar to that of the bilinear transformation but now the mapping is performed only in the -plane: (11.31) where and correspond to the lowpass and resultant filters, respectively, and denotes the transformation operator. To ensure the transformed filter to be stable and causal, the unit circle and inside of the -plane should map into those of the -plane, respectively. H. C. So Page 41 Semester A 2017-2018

Filter Type Lowpass Transformation Operator Design Parameter Highpass Bandpass H. C. So Page 42 Semester A 2017-2018

Bandstop Table 11.1: Frequency band transformation operators Example 11.7 Determine the transfer function of a digital highpass filter whose magnitude requirements are,, db and db. Use the Butterworth lowpass filter and bilinear transformation in the design. Using Example 11.6, the corresponding lowpass filter transfer function is: H. C. So Page 43 Semester A 2017-2018

Assigning the cutoff frequencies as the midpoints between the passband and stopband frequencies, we have With the use of Table 11.1, the corresponding value of is: H. C. So Page 44 Semester A 2017-2018

which gives the transformation operator: As a result, the digital highpass filter transfer function is: The MATLAB program is provided as ex11_7.m. H. C. So Page 45 Semester A 2017-2018

0 Magnitude (db) -8-16 -30 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) 200 Phase (degrees) 150 100 50 0 0 0.2 0.4 0.6 0.8 1 Normalized Frequency ( π rad/samπle) Fig.11.10: Magnitude and phase responses based on frequency band transformation H. C. So Page 46 Semester A 2017-2018