Digital Signal Processing (Paperback)
Language: English
Published by Elsevier Science Publishing Co Inc, San Diego, 2025
- Softcover
- New

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Paperback. Digital Signal Processing: Fundamentals and Applications Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Seller Inventory # 9780443273353
- Title
- Digital Signal Processing (Paperback)
- Author
- Li Tan
- Publisher
- Elsevier Science Publishing Co Inc, San Diego
- Publication year
- 2025
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0443273359
- ISBN 13
- 9780443273353
- Edition
- 4th Edition
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, µ-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks.
- Covers DSP principles with various examples of real-world DSP applications on noise cancellation, communications, control applications, and artificial intelligence
- Includes application examples using DSP techniques for deep learning neural networks to solve real-world problems
- Provides a new chapter to cover principles of artificial neural networks and convolution neural networks with back-propagation algorithms
- Provides hands-on practice, with MATLAB code for worked examples and C programs for real-time DSP for students at https://www.elsevier.com/books-and-journals/book-companion/9780443273353
- Offers teaching support, including an image bank, full solutions manual, and MATLAB projects for qualified instructors, available for request at https://educate.elsevier.com/9780443273353
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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