Digital Signal Processing
Fundamentals, Applications, and Deep Learning
- 4th Edition - February 5, 2025
- Latest edition
- Authors: Li Tan, Jean Jiang
- Language: English
Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of digital signal processing (DSP) whi… Read more
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Description
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, µ-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks.
Key features
Key features
- 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.ucc.idm.oclc.org/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.ucc.idm.oclc.org/9780443273353
Readership
Readership
Table of contents
Table of contents
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
Appendix
A: Introduction to the MATLAB Environment
B: Review of Analog Signal Processing Basics
C: Normalized Butterworth and Chebyshev Functions
D: Sinusoidal Steady-State Response of Digital Filters
E: Filter Design Equations by Frequency Sampling Design Method
F: Wavelet Analysis and Synthesis Equations
G: Review of Discrete-Time Random Signals
H: Some Useful Mathematical Formulas Answers to Selected Problems
Product details
Product details
- Edition: 4
- Latest edition
- Published: March 11, 2025
- Language: English
About the authors
About the authors
LT
Li Tan
JJ