Digital Filters: Principles and Applications with MATLAB (IEEE Series on Digital & Mobile Communication)
The book is not an exposition on digital signal processing (DSP) but rather a treatise on digital filters. The material and coverage is comprehensive, presented in a consistent that first develops topics and subtopics in terms it their purpose, relationship to other core ideas, theoretical and conceptual framework, and finally instruction in the implementation of digital filter devices. Each major study is supported by Matlab-enabled activities and examples, with each Chapter culminating in a comprehensive design case study.
Why Read This Book
You will get a focused, end-to-end treatment of digital filters that ties rigorous theory to practical MATLAB implementations and design case studies. The book shows not only how filters work, but why particular design choices are made and how to realize them in real systems (audio, communications, radar, and speech).
Who Will Benefit
Engineers, researchers, and advanced students who already know basic DSP and want a deep, practical resource for designing, analyzing, and implementing digital filters with MATLAB-driven examples and case studies.
Level: Advanced — Prerequisites: Introductory DSP (discrete-time signals, sampling, z-transform), linear systems theory, basic probability/statistics, linear algebra, and familiarity with MATLAB programming.
Key Takeaways
- Design classic and modern FIR and IIR filters to meet precise frequency-domain specifications.
- Analyze filter performance using spectral analysis and FFT-based techniques and interpret results for system design.
- Implement filters in MATLAB with attention to numerical issues, quantization, and efficient realizations for fixed-point targets.
- Apply adaptive filtering and statistical (Wiener/least-squares) methods to real-world problems like echo cancellation, noise reduction, and channel equalization.
- Use multirate and wavelet-based techniques to build efficient, application-tailored filtering systems for audio, speech, radar, and communications.
- Evaluate and document comprehensive design case studies from specification through MATLAB verification to deployment-ready implementations.
Topics Covered
- 1. Introduction: Role and Scope of Digital Filters
- 2. Mathematical Foundations: z-Transform, Frequency Response, and Stability
- 3. FIR Filter Theory and Design: Windowing, Parks–McClellan, and Frequency Sampling
- 4. IIR Filter Theory and Design: Analog Prototypes, Warping, and Bilinear Transform
- 5. Filter Structures, Realizations, and Numerical Stability
- 6. Spectral Analysis and the FFT: Practical Considerations and Applications
- 7. Multirate Signal Processing and Decimation/Interpolation Filters
- 8. Adaptive Filtering: LMS, RLS, and Practical Adaptation Strategies
- 9. Optimal and Statistical Filtering: Wiener Filters and MMSE Techniques
- 10. Wavelets and Time–Frequency Filtering Methods
- 11. Implementation Issues: Quantization, Fixed-Point Design, and Hardware Considerations
- 12. Application Areas: Audio/Speech, Radar, and Communications Case Studies
- 13. MATLAB-Enabled Examples and Comprehensive Chapter Case Studies
- Appendices: Reference Tables, MATLAB Tips, and Further Reading
Languages, Platforms & Tools
How It Compares
Compared with Oppenheim & Schafer's Discrete-Time Signal Processing (broad DSP foundation), Taylor narrows focus to filters and offers deeper, MATLAB-centric design workflows; compared with Lyons' Understanding Digital Signal Processing (intuitive and example-driven), Taylor is more rigorous and case-study oriented for serious filter design.
