Signal Processing Algorithms in MATLAB (Bk/Disk)
MATLAB is the current "hot" language in signal processing. This book/disk package deails the basic algorithms of digital signal processing, and is written around a set of over 50 MATLAB function m-files, each of which is included on the disk. Emphasizes the application, as opposed to the theory of digital signal processing, covering discrete Fourier transforms, spectral analysis, the frequency and time-domain response of linear systems, digital IIR and FIR filtering; fast convolution and correlation algorithms; least-squares design; adaptive signal processing, and statistical parameters. For signal processing engineers.
Why Read This Book
You will get a hands-on, implementation-first guide to core DSP algorithms with more than 50 ready-to-run MATLAB m-files so you can move quickly from concept to working code. The book emphasizes practical application—FFT/DFT, spectral analysis, digital IIR/FIR filters, fast convolution, least-squares and adaptive methods—making it ideal when you need tested algorithms rather than lengthy proofs.
Who Will Benefit
Signal-processing engineers, graduate students, and practicing scientists who know basic signals theory and want working MATLAB implementations to prototype and test audio, radar, and communications algorithms.
Level: Intermediate — Prerequisites: Undergraduate-level signals & systems and linear algebra; basic MATLAB familiarity (scripts, functions, arrays); basic calculus and probability/statistics.
Key Takeaways
- Implement discrete Fourier transforms and FFT-based processing in MATLAB using supplied m-files
- Design and evaluate digital FIR and IIR filters and analyze their time- and frequency-domain responses
- Apply fast convolution/correlation techniques and use overlap-add/overlap-save methods for efficient filtering
- Develop least-squares and classical spectral estimation methods for parameter estimation and system identification
- Implement adaptive filtering algorithms (e.g., LMS variants) and evaluate their performance on real signals
- Analyze stochastic signal properties and compute statistical signal-processing parameters for communications, audio, and radar applications
Topics Covered
- 1. Introduction to MATLAB for Signal Processing and the Disk of m‑Files
- 2. Discrete-Time Signals and Systems: Representations and Operations
- 3. The Discrete Fourier Transform and FFT Algorithms
- 4. Spectral Analysis and Periodogram Methods
- 5. Time- and Frequency-Domain Response of Linear Systems
- 6. FIR Filter Design and Windowing Techniques
- 7. IIR Filter Design and Realization Forms
- 8. Fast Convolution, Correlation, and Efficient Implementations
- 9. Least-Squares Methods and System Identification
- 10. Adaptive Filtering: LMS and Related Algorithms
- 11. Statistical Signal Processing: Estimators and Performance Measures
- 12. Application Examples: Audio/Speech, Radar, and Communications
- 13. Appendix: MATLAB Function Reference and Using the Distributed m‑Files
Languages, Platforms & Tools
How It Compares
Compared with Proakis & Manolakis (a comprehensive theory-heavy text), Stearns is much more application- and code-oriented; compared with Steven W. Smith's practical DSP guides, Stearns stands out for providing a curated set of MATLAB m‑files tied directly to each topic.
