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Digital Signal Processing: A Practical Approach, 2nd Edition

Emmanuel Ifeachor, Wandel and Goltermann Professor of Intelligent Electronic Systems and Head of the School of Electronic, Communication and Electrical Engineering, University of Plymouth

Barrie Jervis, Wandel and Goltermann Professor of Intelligent Electronic Systems and Head of the School of Electronic, Communication and Electrical Engineering, University of Plymouth

Emmanuel Ifeachor, Wandel and Goltermann Professor of Intelligent Electronic Systems and Head of the School of Electronic, Communication and Electrical Engineering, University of Plymouth

Barrie Jervis, Sheffield Hallam University

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Overview

Description

For undergraduate electrical, electronic or communications engineering courses.

Now in its second edition, Digital Signal Processing offers modern coverage of the fundamentals, implementation and applications of digital signal processing techniques from a practical point of view.
The past ten years has seen a significant growth in DSP applications throughout all areas of technology and this growth is expected well into the next millennium. This successful textbook covers most aspects of DSP found in undergraduate electrical, electronic or communications engineering courses. Unlike many other texts, it also covers a number of DSP techniques which are of particular relevance to industry such as adaptive filtering and multirate processing. The emphasis throughout the book is on the practical aspects of DSP.

Features

NEW - Introductory chapter on analogue I/O design—Illustrates how to obtain digital signals from analogue ones.

NEW - Applications in audio, medical and telecommunications engineering.

NEW - Coverage of DSP system design—Includes the use of MATLAB.

NEW - More applications of multirate processing.

NEW - More hardware included in later chapters—Covering TI and Motorola systems.

Mathematical content reduced to that which is necessary for comprehension of DSP techniques—Also, concepts are illustrated with practically oriented worked examples.

Real-world application examples and end-of-chapter problems.

Realistic examples—Illustrate important concepts and reinforce the knowledge gained.

C language implementation of many DSP algorithms and functions.

New to This Edition

Introductory chapter on analogue I/O design—Illustrates how to obtain digital signals from analogue ones.

Applications in audio, medical and telecommunications engineering.

Coverage of DSP system design—Includes the use of MATLAB.

More applications of multirate processing.

More hardware included in later chapters—Covering TI and Motorola systems.

Typical Real-Time DSP Systems. Analog-to-Digital Conversion Process. Sampling — Lowpass and Bandpass Signals. Uniform and Non-Uniform Quantization and Encoding. Oversampling in A/D Conversion. Digital-to-Analog Conversion Process: Signal Recovery. The DAC. Anti-Imaging Filtering. Oversampling in D/A Conversion. Constraints of Real-Time Processing with Analog Input/Output Signals. Application Examples.

3. Discrete Transforms.

Introduction. DFT and Its Inverse. Properties of the DFT. Computational Complexity of the DFT. The Decimation-in-Time Fast Fourier Transform Algorithm. Inverse Fast Fourier Transform. Implementation of the FFT. Other Discrete Transforms. An Application of the DCT: Image Compression. Worked Examples.

4. The Z-Transform and Its Applications in Signal Processing.

Discrete-Time Signals and Systems. The Z-Transform. The Inverse Z-Transform. Properties of the Z-Transform. Some Applications of the Z-Transform in Signal Processing.

5. Correlation and Convolution.

Introduction. Correlation Description. Convolution Description. Implementation of Correlation and Convolution. Application Examples.

6. A Framework for Digital Filter Design.

Introduction to Digital Filters. Types of Digital Filters: FIR and IIR Filters. Choosing Between FIR and IIR Filters. Filter Design Steps. Illustrative Examples.

7. Finite Impulse Response (FIR) Filter Design.

Introduction. FIR Filter Design. FIR Filter Specifications. FIR Coefficient Calculation Methods. Window Method. The Optimal Method. Frequency Sampling Method. Comparison of the Window, Optimum and Frequency Sampling Methods. Special FIR Filter Design Topics. Realization Structures for FIR Filters. Finite Worldlength Effects in FIR Digital Filters. FIR Implementation Techniques. Design Example. Application Examples of FIR Filters.

8. Design of Infinite Impulse Response (IIR) Digital Filters.

Introduction: Summary of the Basic Features of IIR Filters. Design Stages for Digital IIR Filters. Performance Specification. Coefficient Calculation Methods for IIR Filters. Pole-Zero Placement Method of Coefficient Calculation. Impulse Variant Method of Coefficient Calculation. Matched Z-Transform (MZT) Method of Coefficient Calculation. Bilinear Z-Transform (BZT) Method of Coefficient Calculation. Use of BZT and Classical Analog Filters to Design IIR Filters. Calculating IIR Filter Coefficients by Mapping S-Plane Poles and Zeros. Using IIR Filter Design Programs. Choice of Coefficient Calculation Methods for IIR Filters. Realization Structures for IIR Digital Filters. Finite Worldlength Effects in IIR Filters. Implementation of IIR Filters. A Detailed Design Example of an IIR Digital Filter. Application Examples in Digital Audio and Instrumentation. Application Examples in Telecommunication.

9. Multirate Digital Signal Processing.

Introduction. Concepts of Multirate Signal Processing. Design of Practical Sampling Rate Converters. Software Implementation of Sampling Rate Converters-Decimators. Software Implementation of Interpolators. Sample Rate Conversion Using Polyphase Filter Structure. Application Examples.

10. Adaptive Digital Filters.

When to Use Adaptive Filters and Where They Have Been Used. Concepts of Adaptive Filtering. Basic Wiener Filter Theory. The Basic LMS Adaptive Algorithm. Recursive Least Squares Algorithm. Application Example 1 — Adaptive Filtering of Ocular Artefacts from the Human EEG. Application Example 2 — Adaptive Telephone Echo Cancellation. Other Applications.

11. Spectrum Estimation and Analysis.

Introduction. Principles of Spectrum Estimation. Traditional Methods. Modern Parametric Estimation Methods. Autoregressive Spectrum Estimation. Comparison of Estimation Methods. Application Examples. Worked Example.

12. General- and Special-Purpose Hardware for DSP.

Introduction. Computer Architectures for Signal Processing. General-Purpose Digital Signal Processors. Selecting Digital Signal Processors. Implementation of DSP Algorithms on General-Purpose Digital Signal Processors. Special-Purpose DSP Hardware.

13. Analysis of Finite Wordlength Effects in Fixed-Point DSP Systems.

Introduction. DSP Arithmetic. ADC Quantization Noise and Signal Quality. Finite Worldlength Effects in IIR Digital Filters. Finite Worldlength Effects in FFT Algorithms.

14. Applications and Design Studies.

Evaluation Boards for Real-Time Signal Processing. DSP Applications. Design Studies. Computer-Based Multiple Choice DSP Questions.

Index.

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About the Author(s)

Emmanuel Ifeachor is Professor of Intelligent Electronic Systems and Director of the Centre for Communications, Networks and Information Systems at the University of Plymouth, UK.

Barrie Jervis is Professor of Electronic Engineering at Sheffield Hallam University, UK.

This book evolved from the authors' extensive experience in teaching practically oriented courses in DSP to both undergraduates and engineers in industry. Their own research in applied DSP has influenced the contents of the book and provided many of the examples and case studies.