Digital Filters : Analysis, Design, and Signal Processing Applications / Andreas Antoniou.

Format:

Book

Author/Creator:

Antoniou, Andreas, author.

Language:

English

Subjects (All):

Electric filters, Digital.

Signal processing--Digital techniques.

Signal processing.

Genre:

Electronic books.

Physical Description:

1 online resource

Edition:

2nd edition.

Place of Publication:

New York, N.Y. : McGraw-Hill Education, [2018].

Language Note:

In English.

Summary:

Up-to-date digital filter design principles, techniques, and applications. Written by a Life Fellow of the IEEE, this comprehensive textbook teaches digital filter design, realization, and implementation and provides detailed illustrations and real-world applications of digital filters to signal processing. Digital Filters: Analysis, Design, and Signal Processing Applications gives a solid foundation in the fundamentals and concepts of DSP and continues with state-of-the-art methodologies and algorithms for the design of digital filters. You will get clear explanations of key topics such as spectral analysis, discrete-time systems, and the sampling process. This hands-on resource is supported by a rich collection of online materials that include PDF presentations, detailed solutions of the end-of-chapter problems, MATLAB programs that can be used to analyze and design digital filters of professional quality, and the author's DSP software D-Filter.

Contents:

Cover

Title Page

Copyright Page

Dedication

About the Author

Contents

Preface

1 Introduction to Digital Signal Processing

1.1 Introduction

1.2 Signals

1.3 Frequency-Domain Representation

1.4 Notation

1.5 Signal Processing

1.6 Analog Filters

1.7 Applications of Analog Filters

1.8 Digital Filters

1.9 Three DSP Applications

2 Discrete-Time Systems

2.1 Introduction

2.2 Basic System Properties

2.3 Characterization of Discrete-Time Systems

2.4 Discrete-Time System Networks

2.5 Introduction to Time-Domain Analysis

2.6 Convolution Summation

2.7 Stability

2.8 State-Space Representation

2.9 Problems

3 The Fourier Series and Transform

3.1 Introduction

3.2 Fourier Series

3.3 Fourier Transform

3.4 Interrelation between the Fourier Series and the Fourier Transform

3.5 Poisson?s Summation Formula

3.6 Laplace Transform

3.7 Problems

4 The Z Transform

4.1 Introduction

4.2 Definition of Z Transform

4.3 Convergence Properties

4.4 The Z Transform as a Laurent Series

4.5 Inverse Z Transform

4.6 Additional Theorems and Properties

4.7 Z Transforms of Elementary Discrete-Time Signals

4.8 Z-Transform Inversion Techniques

4.9 Spectral Representation of Discrete-Time Signals

4.10 Problems

5 Application of Transform Theory to Systems

5.1 Introduction

5.2 The Discrete-Time Transfer Function

5.3 Stability

5.4 Time-Domain Analysis

5.5 Frequency-Domain Analysis

5.6 Transfer Functions for Digital Filters

5.7 Amplitude and Delay Distortion

5.8 Continuous-Time Systems

5.9 Problems

6 The Sampling Process

6.1 Introduction

6.2 Impulse-Modulated Signals

6.3 The Sampling Theorem

6.4 Aliasing

6.5 Graphical Representation of Interrelations

6.6 Processing of Continuous-Time Signals Using Digital Filters

6.7 Practical A/D and D/A Converters

6.8 Problems

7 The Discrete Fourier Transform

7.1 Introduction

7.2 Definition

7.3 Inverse DFT

7.4 Properties

7.5 Interrelation between the DFT and the Z Transform

7.6 Interrelation between the DFT and the CFT

7.7 Interrelation between the DFT and the Fourier Series

7.8 Simplified Notation

7.9 Periodic Convolutions

7.10 Fast Fourier-Transform Algorithms

7.11 Application of the FFT Approach to Signal Processing

7.12 Problems

8 The Window Technique

8.1 Introduction

8.2 Basic Principles

8.3 Discrete-Time Windows

8.4 Problems

9 Realization of Digital Filters

9.1 Introduction

9.2 Realization

9.3 Implementation

9.4 Problems

10 Design of Nonrecursive Filters

10.1 Introduction

10.2 Properties of Constant-Delay Nonrecursive Filters

10.3 Design Using the Fourier Series

10.4 Use of Window Technique

10.5 Prescribed Filter Specifications

10.6 Design Based on Numerical-Analysis Formulas

10.7 Problems

11 Approximations for Analog Filters

11.1 Introduction

11.2 Basic Concepts

11.3 Butterworth Approximation

11.4 Chebyshev Approximation

11.5 Inverse-Chebyshev Approximation

11.6 Elliptic Approximation

11.7 Bessel-Thomson Approximation

11.8 Transformations

11.9 Problems

12 Design of Recursive Filters

12.1 Introduction

12.2 Realizability Constraints.

12.3 Invariant Impulse-Response Method

12.4 Modified Invariant Impulse-Response Method

12.5 Matched-Z Transformation Method

12.6 Bilinear-Transformation Method

12.7 Digital-Filter Transformations

12.8 Comparison between Recursive and Nonrecursive Designs

12.9 Problems

13 Recursive Filters Satisfying Prescribed Specifications

13.1 Introduction

13.2 Design Procedure

13.3 Design Formulas

13.4 Design Using the Formulas and Tables

13.5 Constant Group Delay

13.6 Amplitude-Response Equalization

13.7 Problems

14 Effects of Finite Word Length in Digital Filters

14.1 Introduction

14.2 Number Representation

14.3 Coefficient Quantization

14.4 Low-Sensitivity Structures

14.5 Product Quantization

14.6 Signal Scaling

14.7 Minimization of Output Roundoff Noise

14.8 Limit-Cycle Oscillations

14.9 Problems

15 Design of Nonrecursive Filters Using Optimization Methods

15.1 Introduction

15.2 Problem Formulation

15.3 Remez Exchange Algorithm

15.4 Improved Search Methods

15.5 Efficient Remez Exchange Algorithm

15.6 Gradient Information

15.7 Prescribed Specifications

15.8 Generalization

15.9 Digital Differentiators

15.10 Arbitrary Amplitude Responses

15.11 Multiband Filters

15.12 Problems

16 Design of Recursive Filters Using Unconstrained Optimization

16.1 Introduction

16.2 Problem Formulation

16.3 Newton?s Method

16.4 Quasi-Newton Algorithms

16.5 Minimax Algorithms

16.6 Improved Minimax Algorithms

16.7 Design of Recursive Filters

16.8 Design of Recursive Delay Equalizers

16.9 Problems

17 Design of Recursive Filters Using Constrained Optimization

17.1 Introduction

17.2 Design Problem

17.3 Constrained Optimization Problem

17.4 Design Procedure

17.5 Alternative Initialization Approaches

17.6 Comparison of Recursive versus Nonrecursive Digital Filters

17.7 Problems

18 Wave Digital Filters

18.1 Introduction

18.2 Sensitivity Considerations

18.3 Wave Network Characterization

18.4 Element Realizations

18.5 Lattice Wave Digital Filters

18.6 Ladder Wave Digital Filters

18.7 Filters Satisfying Prescribed Specifications

18.8 Frequency-Domain Analysis

18.9 Scaling

18.10 Elimination of Limit-Cycle Oscillations

18.11 Related Synthesis Methods

18.12 A Cascade Synthesis Based on the Wave Characterization

18.13 Choice of Structure

18.14 Problems

19 Signal Processing Applications

19.1 Introduction

19.2 Sampling-Frequency Conversion

19.3 Quadrature-Mirror-Image Filter Banks

19.4 Hilbert Transformers

19.5 Two-Dimensional Digital Filters

19.6 Adaptive Digital Filters

19.7 Problems

Appendix: Complex Analysis

A.1 Introduction

A.2 Complex Numbers

A.3 Functions of a Complex Variable

A.4 Basic Principles of Complex Analysis

A.5 Series

A.6 Laurent Theorem

A.7 Residue Theorem

A.8 Analytic Continuation

A.9 Conformal Transformations

References

Index

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

Q

R

S

T

U

V

W

Z.

Notes:

Includes bibliographical references and index.

Electronic reproduction. New York, N.Y. : McGraw Hill, 2018. Mode of access: World Wide Web. System requirements: Web browser. Access may be restricted to users at subscribing institutions.

Description based on e-Publication PDF.

Other Format:

Print version: Digital Filters : Analysis, Design, and Signal Processing Applications

ISBN:

9780071846042 (e-ISBN)

0071846042 (e-ISBN)

9780071846035 (print-ISBN)

0071846034 (print-ISBN)

OCLC:

1021059795

Access Restriction:

Restricted for use by site license.