Digital Signal Processing

Digital Signal Processing

Fundamentals and Applications

First published on January 21, 2013

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  • Authors: Lizhe Tan, Jean Jiang
  • eBook ISBN: 9780124159822

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Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers. The book goes beyond DSP theory, to show implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, u-law, ADPCM, and multi-rate DSP and over-sampling ADC. New to this edition: MATLAB projects dealing with practical applications added throughout the book New chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP field New applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signals All real-time C programs revised for the TMS320C6713 DSK

Key Features

  • Covers DSP principles with emphasis on communications and control applications
  • Chapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problems
  • Website with MATLAB programs for simulation and C programs for real-time DSP


This book is targeted to meet the needs of electrical engineers and technicians who design and build hardware and software for DSP systems. 

This textbook can also be used in an introductory DSP course at the junior level in undergraduate electrical engineering program at traditional colleges. Additionally, the book should be useful as a reference for undergraduate engineering students, science students, and practicing engineers

Table of Contents

  • Preface

    Chapter 1. Introduction to Digital Signal Processing


    1.1 Basic Concepts of Digital Signal Processing

    1.2 Basic Digital Signal Processing Examples in Block Diagrams

    1.3 Overview of Typical Digital Signal Processing in Real-World Applications

    1.4 Digital Signal Processing Applications

    1.5 Summary

    Chapter 2. Signal Sampling and Quantization


    2.1 Sampling of Continuous Signal

    2.2 Signal Reconstruction

    2.3 Analog-to-Digital Conversion, Digital-to-Analog Conversion, and Quantization

    2.4 Summary

    2.5 MATLAB Programs

    Chapter 3. Digital Signals and Systems


    3.1 Digital Signals

    3.2 Linear Time-Invariant, Causal Systems

    3.3 Difference Equations and Impulse Responses

    3.4 Bounded-In and Bounded-Out Stability

    3.5 Digital Convolution

    3.6 Summary

    Chapter 4. Discrete Fourier Transform and Signal Spectrum


    4.1 Discrete Fourier Transform

    4.2 Amplitude Spectrum and Power Spectrum

    4.3 Spectral Estimation Using Window Functions

    4.4 Application to Signal Spectral Estimation

    4.5 Fast Fourier Transform

    4.6 Summary

    Chapter 5. The z-Transform


    5.1 Definition

    5.2 Properties of the z-Transform

    5.3 Inverse z-Transform

    5.4 Solution of Difference Equations Using the z-Transform

    5.5 Summary

    Chapter 6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations


    6.1 The Difference Equation and Digital Filtering

    6.2 Difference Equation and Transfer Function

    6.3 The z-Plane Pole-Zero Plot and Stability

    6.4 Digital Filter Frequency Response

    6.5 Basic Types of Filtering

    6.6 Realization of Digital Filters

    6.7 Application: Signal Enhancement and Filtering

    6.8 Summary

    Chapter 7. Finite Impulse Response Filter Design


    7.1 Finite Impulse Response Filter Format

    7.2 Fourier Transform Design

    7.3 Window Method

    7.4 Applications: Noise Reduction and Two-Band Digital Crossover

    7.5 Frequency Sampling Design Method

    7.6 Optimal Design Method

    7.7 Realization Structures of Finite Impulse Response Filters

    7.8 Coefficient Accuracy Effects on Finite Impulse Response Filters

    7.9 Summary of FIR Design Procedures and Selection of FIR Filter Design Methods in Practice

    7.10 Summary

    7.11 MATLAB Programs

    Chapter 8. Infinite Impulse Response Filter Design


    8.1 Infinite Impulse Response Filter Format

    8.2 Bilinear Transformation Design Method

    8.3 Digital Butterworth and Chebyshev Filter Designs

    8.4 Higher-Order Infinite Impulse Response Filter Design Using the Cascade Method

    8.5 Application: Digital Audio Equalizer

    8.6 Impulse-Invariant Design Method

    8.7 Pole-Zero Placement Method for Simple Infinite Impulse Response Filters

    8.8 Realization Structures of Infinite Impulse Response Filters

    8.9 Application: 60-Hz Hum Eliminator and Heart Rate Detection Using Electrocardiography

    8.10 Coefficient Accuracy Effects on Infinite Impulse Response Filters

    8.11 Application: Generation and Detection of DTMF Tones Using the Goertzel Algorithm

    8.12 Summary of Infinite Impulse Response (IIR) Design Procedures and Selection of the IIR Filter Design Methods in Practice

    8.13 Summary

    Chapter 9. Hardware and Software for Digital Signal Processors


    9.1 Digital Signal Processor Architecture

    9.2 Digital Signal Processor Hardware Units

    9.3 Digital Signal Processors and Manufacturers

    9.4 Fixed-Point and Floating-Point Formats

    9.5 Finite Impulse Response and Infinite Impulse Response Filter Implementations in Fixed-Point Systems

    9.6 Digital Signal Processing Programming Examples

    9.7 Summary

    Chapter 10. Adaptive Filters and Applications


    10.1 Introduction to Least Mean Square Adaptive Finite Impulse Response Filters

    10.2 Basic Wiener Filter Theory and Least Mean Square Algorithm

    10.3 Applications: Noise Cancellation, System Modeling, and Line Enhancement

    10.4 Other Application Examples

    10.5 Laboratory Examples Using the TMS320C6713 DSK

    10.6 Summary

    Chapter 11. Waveform Quantization and Compression


    11.1 Linear Midtread Quantization

    11.2 μ-law Companding

    11.3 Examples of Differential Pulse Code Modulation (DPCM), Delta Modulation, and Adaptive DPCM G.721

    11.4 Discrete Cosine Transform, Modified Discrete Cosine Transform, and Transform Coding in MPEG Audio

    11.5 Laboratory Examples of Signal Quantization Using the TMS320C6713 DSK

    11.6 Summary

    11.7 MATLAB Programs

    Chapter 12. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals


    12.1 Multirate Digital Signal Processing Basics

    12.2 Polyphase Filter Structure and Implementation

    12.3 Oversampling of Analog-to-Digital Conversion

    12.4 Application Example: CD Player

    12.5 Undersampling of Bandpass Signals

    12.6 Sampling Rate Conversion Using the TMS320C6713 DSK

    12.7 Summary

    Chapter 13. Subband- and Wavelet-Based Coding


    13.1 Subband Coding Basics

    13.2 Subband Decomposition and Two-Channel Perfect Reconstruction Quadrature Mirror Filter Bank

    13.3 Subband Coding of Signals

    13.4 Wavelet Basics and Families of Wavelets

    13.5 Multiresolution Equations

    13.6 Discrete Wavelet Transform

    13.7 Wavelet Transform Coding of Signals

    13.8 MATLAB Programs

    13.9 Summary

    Chapter 14. Image Processing Basics


    14.1 Image Processing Notation and Data Formats

    14.2 Image Histogram and Equalization

    14.3 Image Level Adjustment and Contrast

    14.4 Image Filtering Enhancement

    14.5 Image Pseudo-Color Generation and Detection

    14.6 Image Spectra

    14.7 Image Compression by Discrete Cosine Transform

    14.8 Creating a Video Sequence by Mixing Two Images

    14.9 Video Signal Basics

    14.10 Motion Estimation in Video

    14.11 Summary

    Appendix A. Introduction to the MATLAB Environment

    A.1 Basic Commands and Syntax

    A.2 MATLAB Arrays and Indexing

    A.3 Plot Utilities: subplot, plot, stem, and stair

    A.4 MATLAB Script Files

    A.5 MATLAB Functions

    Appendix B. Review of Analog Signal Processing Basics

    B.1 Fourier Series and Fourier Transform

    B.2 Laplace Transform

    B.3 Poles, Zeros, Stability, Convolution, and Sinusoidal Steady-State Response

    Appendix C. Normalized Butterworth and Chebyshev Functions

    C.1 Normalized Butterworth Function

    C.2 Normalized Chebyshev Function

    Appendix D. Sinusoidal Steady-State Response of Digital Filters

    D.1 Sinusoidal Steady-State Response

    Appendix E. Finite Impulse Response Filter Design Equations by the Frequency Sampling Design Method

    Appendix F. Wavelet Analysis and Synthesis Equations

    F.1 Basic Properties

    F.2 Analysis Equations

    F.2 Wavelet Synthesis Equations

    Appendix G. Some Useful Mathematical Formulas

    Appendix 8. Answers to Selected Problems

    Chapter 2

    Chapter 3

    Chapter 4

    Chapter 5

    Chapter 6

    Chapter 7

    Chapter 8

    Chapter 9

    Chapter 10

    Chapter 11

    Chapter 12

    Chapter 13

    Chapter 14

    Appendix B



Product details

  • No. of pages: 896
  • Language: English
  • Copyright: © Academic Press 2013
  • Published: January 21, 2013
  • Imprint: Academic Press
  • eBook ISBN: 9780124159822

About the Authors

Lizhe Tan

Lizhe Tan is a professor in the Department of Electrical and Computer Engineering at Purdue University Northwest. He received his Ph.D. degree in Electrical Engineering from the University of New Mexico, Albuquerque, in 1992. Dr. Tan has extensively taught signals and systems, digital signal processing, analog and digital control systems, and communication systems for many years. He has published a number of refereed technical articles in journals, conference papers and book chapters in the areas of digital signal processing. He has authored and co-authored 4 textbooks, and holds a US patent. Dr. Tan is a senior member of the IEEE and has served as an associate editor for several engineering journals.

Affiliations and Expertise

Professor, Electrical Engineering, Purdue University Northwest, IN, USA

Jean Jiang

Jean Jiang is an associate professor in the Department of Engineering Technology at Purdue University Northwest. She received her Ph.D. degree in Electrical Engineering from the University of New Mexico, Albuquerque, in 1992. Dr. Jiang has taught digital signal processing, control systems and communication systems for many years. She has published a number of refereed technical articles in journals, conference papers and book chapters in the area of digital signal processing, and co-authored 4 textbooks. Dr. Jiang is a senior member of the IEEE.

Affiliations and Expertise

Engineering Technology, Purdue University Northwest, IN, USA

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