A Digital Signal Processing Primer: With Applications to Digital Audio and Computer Music
This book by Ken Steiglitz is directed to the new market of DSP users brought about by the development of powerful and inexpensive software tools to analyze signals. These new tools allow sophisticated manipulation of signals but do not provide an understanding of the theory or the foundation for the techniques. This easy-to-understand introduction develops an intuitive approach to the development of the mathematics of DSP and uses examples from areas of the spectrum familiar to beginners together with thought provoking questions and suggested experiments.
Why Read This Book
You should read this book if you want a gentle, intuitive entry into digital signal processing that ties core theory directly to audio and computer-music examples. It emphasizes understanding the mathematics behind common DSP tools and gives thought-provoking experiments you can try with MATLAB/Octave or similar software.
Who Will Benefit
Students, audio engineers, musicians, and hobbyist programmers who need a practical, low-friction introduction to DSP concepts applied to digital audio and music.
Level: Beginner — Prerequisites: Basic calculus and algebra; familiarity with basic programming (MATLAB, Python, or similar) is helpful but not strictly required.
Key Takeaways
- Explain the sampling theorem and how to move between continuous and discrete signals.
- Compute and interpret the DFT/FFT for spectral analysis and practical audio applications.
- Design and apply basic FIR and IIR filters for audio processing tasks.
- Apply windowing and spectral-estimation techniques to obtain reliable frequency-domain results.
- Implement common audio DSP effects (e.g., filtering, delay-based effects, resampling) and test them with simple experiments.
- Translate mathematical descriptions of DSP operations into practical algorithms you can run in MATLAB/Octave or equivalent tools.
Topics Covered
- 1. Introduction to Signals and Systems in Audio
- 2. Sampling and the Discrete-Time Signal
- 3. Time-Domain Representation and Difference Equations
- 4. The z-Transform and System Analysis
- 5. Fourier Series, Fourier Transform and the DFT
- 6. FFT Algorithms and Efficient Computation
- 7. Windowing and Spectral Analysis
- 8. FIR and IIR Filter Design Basics
- 9. Applications to Digital Audio and Computer Music
- 10. Practical Experiments and Software-Based Explorations
- Appendix: Mathematical Background and Suggested Projects
Languages, Platforms & Tools
How It Compares
More approachable and application-focused than Oppenheim & Schafer's Discrete-Time Signal Processing and less exhaustive mathematically than Proakis & Manolakis; similar in spirit to Richard Lyons' Understanding Digital Signal Processing but with a clearer emphasis on audio/music examples.
