Digital Signal Processing: A Practical Approach (Electronic Systems Engineering)
The widespread use of Digital Signal Processing (DSP) techniques in engineering has made their understanding and mastery vital for today's electrical and electronic engineer. Aiming to bridge the gap between theory and practical implementation, this book provides a thorough understanding of the principles and applications of DSP. The mathematical content has been reduced to what is essential and useful. Providing insight and practical guidance throughout, the book shows how DSP techniques can be used to design engineering systems.
Why Read This Book
You will learn practical, implementation-focused DSP techniques that bridge textbook theory and real engineering practice, with emphasis on designing and realising working systems. The book pares back unnecessary mathematics and focuses on the essential tools, examples, and implementation issues you need for audio, speech, radar and communications applications.
Who Will Benefit
Intermediate electrical or electronic engineers and graduate students who need a hands‑on, application-oriented guide to designing and implementing DSP algorithms for real systems.
Level: Intermediate — Prerequisites: Basic calculus and linear algebra, an understanding of continuous and discrete signals and systems, and some experience with programming (MATLAB or C preferred).
Key Takeaways
- Design efficient FIR and IIR digital filters for audio, communications and radar applications
- Apply FFT and DFT methods to practical spectral analysis and implement fast algorithms
- Implement adaptive filters for noise cancellation and system identification
- Analyse quantisation and finite‑word‑length effects and mitigate implementation artefacts
- Develop practical signal processing chains for speech/audio and basic radar/communications tasks
Topics Covered
- 1. Introduction to Digital Signal Processing and Practical Considerations
- 2. Discrete‑Time Signals and Systems; Sampling and Reconstruction
- 3. z‑Transform, Pole‑Zero Analysis and System Stability
- 4. The Discrete Fourier Transform and the Fast Fourier Transform
- 5. Spectral Analysis and Windowing Techniques
- 6. FIR Filter Design and Implementation
- 7. IIR Filter Design, Realisation Forms and Stability
- 8. Multirate Signal Processing and Filter Banks
- 9. Adaptive Filtering: LMS, RLS and Applications
- 10. Statistical Signal Processing and Estimation
- 11. Audio and Speech Processing Techniques
- 12. Radar and Communications Signal Processing Applications
- 13. Implementation Issues: Fixed‑Point Arithmetic, Quantisation and Real‑Time Systems
- 14. Emerging Topics: Time–Frequency Methods and Wavelet Concepts
- Appendices: Mathematical Background and Practical Worked Examples
Languages, Platforms & Tools
How It Compares
More implementation‑focused than Oppenheim & Schafer's Discrete‑Time Signal Processing and more applied and comprehensive for engineering systems than Lyons' Understanding Digital Signal Processing.
