Digital filter design and realization / Takao Hinamoto, Wu-Sheng Lu.

Analysis, design, and realization of digital filters have experienced major developments since the 1970s, and have now become an integral part of the theory and practice in the field of contemporary digital signal processing. Digital Filter Design and Realization is written to present an up-to-date...

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Bibliographic Details
Main Authors:	Hinamoto, Takao (Author), Lu, Wusheng (Author)
Format:	eBook
Language:	English
Published:	Aalborg : River Publishers, 2017.
Series:	River Publishers series in signal, image and speech processing.
Subjects:	Electric filters, Digital. Signal processing > Digital techniques. SCIENCE / Energy TECHNOLOGY / Electricity TECHNOLOGY / Electronics / General Electric filters, Digital Signal processing > Digital techniques Electronic books.
Online Access:	Click for online access

Table of Contents:

Front Cover
Half Title Page
RIVER PUBLISHERS SERIES IN SIGNAL, IMAGE AND SPEECH PROCESSING
Title Page
Digital Filter Design and Realization
Copyright Page
Contents
Preface
List of Figures
List of Tables
List of Abbreviations
Chapter 1
Introduction
1.1 Preview
1.2 Terminology for Signal Analysis and Typical Signals
1.2.1 Terminology for Signal Analysis
1.2.2 Examples of Typical Signals
1.3 Digital Signal Processing
1.3.1 General Framework for Digital Signal Processing
1.3.2 Advantages of Digital Signal Processing
1.3.3 Disadvantages of Digital Signal Processing
1.4 Analysis of Analog Signals
1.4.1 The Fourier Series Expansion of Periodic Signals
1.4.2 The Fourier Transform
1.4.3 The Laplace Transform
1.5 Analysis of Discrete-Time Signals
1.5.1 Sampling an Analog Signal
1.5.2 The Discrete-Time Fourier Transform
1.5.3 The Discrete Fourier Transform (DFT)
1.5.4 The z-Transform
1.6 Sampling of Continuous-Time Sinusoidal Signals
1.7 Aliasing
1.8 Sampling Theorem
1.9 Recovery of an Analog Signal
1.10 Summary
References
Chapter 2
Discrete-Time Systems and z-Transformation
2.1 Preview
2.2 Discrete-Time Signals
2.3 z-Transform of Basic Sequences
2.3.1 Fundamental Transforms
2.3.2 Properties of z-Transform
2.4 Inversion of z-Transforms
2.4.1 Partial Fraction Expansion
2.4.2 Power Series Expansion
2.4.3 Contour Integration
2.5 Parseval's Theorem
2.6 Discrete-Time Systems
2.7 Difference Equations
2.8 State-Space Descriptions
2.8.1 Realization 1
2.8.2 Realization 2
2.9 Frequency Transfer Functions
2.9.1 Linear Time-Invariant Causal Systems
2.9.2 Rational Transfer Functions
2.9.3 All-Pass Digital Filters
2.9.4 Notch Digital Filters
2.9.5 Doubly Complementary Digital Filters
2.10 Summary.
5.9.2 Analytical Approach
5.9.2.1 General FIR filter design
5.9.2.2 Linear-Phase FIR filter design
5.9.3 Chebyshev Approximation
5.9.4 Comparison of Algorithms' Performances
5.10 Summary
References
Chapter 6
Design Methods Using Analog Filter Theory
6.1 Preview
6.2 Design Methods Using Analog Filter Theory
6.2.1 Lowpass Analog-Filter Approximations
6.2.1.1 Butterworth approximation
6.2.1.2 Chebyshev approximation
6.2.1.3 Inverse-Chebyshev approximation
6.2.1.4 Elliptic approximation
6.2.2 Other Analog-Filter Approximations by Transformations
6.2.2.1 Lowpass-to-lowpass transformation
6.2.2.2 Lowpass-to-highpass transformation
6.2.2.3 Lowpass-to-bandpass transformation
6.2.2.4 Lowpass-to-bandstop transformation
6.2.3 Design Methods Based on Analog Filter Theory
6.2.3.1 Invariant impulse-response method
6.2.3.2 Bilinear-transformation method
6.3 Summary
References
Chapter 7
Design Methods in the Frequency Domain
7.1 Preview
7.2 Design Methods in the Frequency Domain
7.2.1 Minimum Mean Squared Error Design
7.2.2 An Equiripple Design by Linear Programming
7.2.3 Weighted Least-Squares Design with Stability Constraints
7.2.4 Minimax Design with Stability Constraints
7.3 Design of All-Pass Digital Filters
7.3.1 Design of All-Pass Filters Based on Frequency Response Error
7.3.2 Design of All-Pass Filters Based on Phase Characteristic Error
7.3.3 A Numerical Example
7.4 Summary
References
Chapter 8
Design Methods in the Time Domain
8.1 Preview
8.2 Design Based on Extended Pade's Approximation
8.2.1 A Direct Procedure
8.2.2 A Modified Procedure
8.3 Design Using Second-Order Information
8.3.1 A Filter Design Method
8.3.2 Stability
8.3.3 An Efficient Algorithm for Solving (8.35)
8.4 Least-Squares Design.
8.5 Design Using State-Space Models
8.5.1 Balanced Model Reduction
8.5.2 Stability and Minimality
8.6 Numerical Experiments
8.6.1 Design Based on Extended Pade's Approximation
8.6.2 Design Using Second-Order Information
8.6.3 Least-Squares Design
8.6.4 Design Using State-Space Model (Balanced Model Reduction)
8.6.5 Comparison of Algorithms' Performances
8.7 Summary
References
Chapter 9
Design of Interpolated and FRM FIR Digital Filters
9.1 Preview
9.2 Basics of IFIR and FRM Filters and CCP
9.2.1 Interpolated FIR Filters
9.2.2 Frequency-Response-Masking Filters
9.2.3 Convex-Concave Procedure (CCP)
9.3 Minimax Design of IFIR Filters
9.3.1 Problem Formulation
9.3.2 Convexification of (9.10) Using CCP
9.3.3 Remarks on Convexification in (9.13)-(9.14)
9.4 Minimax Design of FRM Filters
9.4.1 The Design Problem
9.4.2 A CCP Approach to Solving (9.23)
9.5 FRM Filters with Reduced Complexity
9.5.1 Design Phase 1
9.5.2 Design Phase 2
9.6 Design Examples
9.6.1 Design and Evaluation Settings
9.6.2 Design of IFIR Filters
9.6.3 Design of FRM Filters
9.6.4 Comparisons with Conventional FIR Filters
9.7 Summary
References
Chapter 10
Design of a Class of Composite Digital Filters
10.1 Preview
10.2 Composite Filters and Problem Formulation
10.2.1 Composite Filters
10.2.2 Problem Formulation
10.3 Design Method
10.3.1 Design Strategy
10.3.2 Solving (10.7) with y Fixed to y = yk
10.3.3 Updating y with x Fixed to x = xk
10.3.4 Summary of the Algorithm
10.4 Design Example and Comparisons
10.5 Summary
References
Chapter 11
FiniteWord Length Effects
11.1 Preview
11.2 Fixed-Point Arithmetic
11.3 Floating-Point Arithmetic
11.4 Limit Cycles-Overflow Oscillations.
11.5 Scaling Fixed-Point Digital Filters to Prevent Overflow
11.6 Roundoff Noise
11.7 Coefficient Sensitivity
11.8 State-Space Descriptions with FiniteWord Length
11.9 Limit Cycle-Free Realization
11.10 Summary
References
Chapter 12
l2-Sensitivity Analysis and Minimization
12.1 Preview
12.2 l2-Sensitivity Analysis
12.3 Realization with Minimal l2-Sensitivity
12.4 l2-Sensitivity Minimization Subject to l2-Scaling Constraints Using Quasi-Newton Algorithm
12.4.1 l2-Scaling and Problem Formulation
12.4.2 Minimization of (12.18) Subject to l2-Scaling Constraints
Using Quasi-Newton Algorithm
12.4.3 Gradient of J(x)
12.5 l2-Sensitivity Minimization Subject to l2-Scaling Constraints Using Lagrange Function
12.5.1 Minimization of (12.19) Subject to l2-Scaling Constraints
Using Lagrange Function
12.5.2 Derivation of Nonsingular T from P to Satisfy l2-Scaling Constraints
12.6 Numerical Experiments
12.6.1 Filter Description and Initial l2-Sensitivity
12.6.2 l2-Sensitivity Minimization
12.6.3 l2-Sensitivity Minimization Subject to l2-Scaling Constraints Using Quasi-Newton Algorithm
12.6.4 l2-Sensitivity Minimization Subject to l2-Scaling Constraints Using Lagrange Function
12.7 Summary
References
Chapter 13
Pole and Zero Sensitivity Analysis and Minimization
13.1 Preview
13.2 Pole and Zero Sensitivity Analysis
13.3 Realization with Minimal Pole and Zero Sensitivity
13.3.1 Weighted Pole and Zero Sensitivity Minimization WithoutImposing l2-Scaling Constraints
13.3.2 Zero Sensitivity Minimization Subject to Minimal Pole Sensitivity
13.4 Pole Zero Sensitivity Minimization Subject to l2-Scaling Constraints Using Lagrange Function
13.4.1 l2-Scaling Constraints and Problem Formulation.
13.4.2 Minimization of (13.37) Subject to l2-Scaling Constraints
Using Lagrange Function.

Digital filter design and realization / Takao Hinamoto, Wu-Sheng Lu.

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