Description

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

Table of Contents

Preface

Chapter 1. Introduction to Digital Signal Processing

Objectives

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

Objectives

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

Objectives

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

Objectives

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

Objectives

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

Objectives:

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 an

Details

No. of pages:
896
Language:
English
Copyright:
© 2013
Published:
Imprint:
Academic Press
eBook ISBN:
9780124159822
Print ISBN:
9780124158931

Reviews

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