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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
- 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
Readership
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
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 and Filtering
6.8 Summary
Chapter 7. Finite Impulse Response Filter Design
Objectives:
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
OBJECTIVES:
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
Objectives
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
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9.6 Digital Signal Processing Programming Examples
9.7 Summary
Chapter 10. Adaptive Filters and Applications
Objectives
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
Digital Signal Processing Salivahanan
10.4 Other Application Examples
10.5 Laboratory Examples Using the TMS320C6713 DSK
10.6 Summary
Chapter 11. Waveform Quantization and Compression
Objectives
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
Objectives
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
Objectives
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
Objectives
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
References
Index
Details
- No. of pages:
- 896
- Language:
- English
- Copyright:
- © Academic Press 2013
Digital Signal Processing Salivahanan Ebook Login Free
- Published:
- 8th February 2013
- Imprint:
- Academic Press
- eBook ISBN:
- 9780124159822
- Hardcover ISBN:
- 9780124158931
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.
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.
Engineering Technology, Purdue University Northwest, IN, USA
Ratings and 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