Digital Signal Processing
Fundamentals, Applications, and Deep Learning
4th Edition
Published on 23. May 2025
Book
Paperback/Softback
1032 pages
978-0-443-27335-3 (ISBN)
Description
Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of digital signal processing (DSP) while also providing a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers.
This book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include DSP for artificial intelligence, 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 pulse-code modulation, ?-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks.
This book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include DSP for artificial intelligence, 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 pulse-code modulation, ?-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks.
More details
Edition
4th edition
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Dimensions
Height: 233 mm
Width: 188 mm
Thickness: 50 mm
Weight
2044 gr
ISBN-13
978-0-443-27335-3 (9780443273353)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Electrical Engineering Tan | Electrical Engineering Jiang
Digital Signal Processing
Fundamentals, Applications, and Deep Learning
E-Book
02/2025
4th Edition
Academic Press
€89.99
Available for download
Previous edition
Book
11/2018
3rd Edition
Academic Press
€86.65
Article exhausted; check for reprint
Persons
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. 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.
Content
1. Introduction to Digital Signal Processing
2. Signal Sampling and Quantization
3. Digital Signals and Systems
4. Discrete Fourier Transform and Signal Spectra
5. The z-Transform
6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations
7. Finite Impulse Response Filter Design
8. Infinite Impulse Response Filter Design
9. Adaptive Filters and Applications
10. Waveform Quantization and Compression
11. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals
12. Subband and Wavelet-Based Coding
13. Image Processing Basics
14. Digital Signal Processing for Artificial Intelligence
15. Hardware and Software for Digital Signal Processors
2. Signal Sampling and Quantization
3. Digital Signals and Systems
4. Discrete Fourier Transform and Signal Spectra
5. The z-Transform
6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations
7. Finite Impulse Response Filter Design
8. Infinite Impulse Response Filter Design
9. Adaptive Filters and Applications
10. Waveform Quantization and Compression
11. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals
12. Subband and Wavelet-Based Coding
13. Image Processing Basics
14. Digital Signal Processing for Artificial Intelligence
15. Hardware and Software for Digital Signal Processors