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Full 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.
Contents
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
