Digital Signal Processing: A Practical Guide for Engineers and Scientists
In addition to its thorough coverage of DSP design and programming techniques, Smith also covers the operation and usage of DSP chips. He uses Analog Devices' popular DSP chip family as design examples. Also included on the companion website is technical info on DSP processors from the four major manufacturers (Analog Devices, Texas Instruments, Motorola, and Lucent) and other DSP software.
*Covers all major DSP topics
*Full of insider information and shortcuts
*Basic techniques and algorithms explained without complex numbers
Why Read This Book
You should read this book if you want a hands-on, non‑mathematical introduction to the DSP algorithms and implementation tricks practiced in industry; it translates DSP theory into working recipes, code examples, and processor-aware guidance. You will get practical shortcuts, clear explanations of FFTs and filters, and concrete advice for running DSP code on real chips.
Who Will Benefit
Practicing engineers, advanced students, and hobbyists who need to implement DSP algorithms (filters, FFT-based analysis, spectral methods) on general-purpose or dedicated DSP processors.
Level: Intermediate — Prerequisites: Basic calculus and complex numbers, introductory signals & systems concepts (sampling, convolution), and some programming experience (C or MATLAB/pseudocode).
Key Takeaways
- Implement and interpret FFT-based spectral analysis and windowing techniques in practical applications.
- Design and deploy FIR and IIR filters using window methods, bilinear transform, and common tuning heuristics.
- Apply sampling, aliasing, decimation and interpolation correctly in signal chain designs.
- Manage fixed-point arithmetic and processor constraints when porting algorithms to real DSP chips.
- Optimize DSP code for target processors by using practical tips, examples, and processor-specific considerations.
- Use common DSP algorithms for audio and general signal processing tasks with clear, working examples.
Topics Covered
- Introduction and DSP basics (signals, sampling, convolution)
- Frequency domain concepts and the Fourier transform
- The Discrete Fourier Transform and FFT algorithms
- Windowing and spectral analysis (leakage, resolution)
- Digital filter fundamentals (FIR and IIR overview)
- FIR filter design and implementation (window methods)
- IIR filter design and implementation (bilinear transform, stability)
- Multirate basics: decimation and interpolation
- Practical issues: quantization, fixed-point arithmetic, and numerical errors
- Implementation on DSP hardware: architectures and trade-offs
- Processor examples and code snippets (Analog Devices, TI, Motorola)
- Application examples: audio, basic communications, and measurement
Languages, Platforms & Tools
How It Compares
More practical and less mathematically rigorous than Oppenheim & Schafer's Discrete‑Time Signal Processing; similar in accessibility to Richard Lyons' Understanding Digital Signal Processing but with more emphasis on real DSP chips and implementation tips.
