Digital Signal Processing : A Computer Based Approach
Digital Signal Processing: A Computer-Based Approach is intended for a two-semester course on digital signal processing for seniors or first-year graduate students. Based on user feedback, a number of new topics have been added to the third edition, while some excess topics from the second edition have been removed. The author has taken great care to organize the chapters more logically by reordering the sections within chapters. More worked-out examples have also been included. The book contains more than 500 problems and 150 MATLAB exercises.
New topics in the third edition include: short-time characterization of discrete-time signals, expanded coverage of discrete-time Fourier transform and discrete Fourier transform, prime factor algorithm for DFT computation, sliding DFT, zoom FFT, chirp Fourier transform, expanded coverage of z-transform, group delay equalization of IIR digital filters, design of computationally efficient FIR digital filters, semi-symbolic analysis of digital filter structures, spline interpolation, spectral factorization, discrete wavelet transform.
Why Read This Book
You will get a comprehensive, MATLAB-centered introduction to modern digital signal processing that balances theory with hands-on computation and hundreds of worked examples. The book's strengths are its broad coverage (from FFTs and filter design to wavelets and adaptive filtering), extensive MATLAB exercises on the bundled CD-ROM, and clear, application-oriented explanations that prepare you to implement DSP algorithms for audio, radar, and communications.
Who Will Benefit
Senior undergraduates, first-year graduate students, and practicing engineers who want an application-focused, computation-driven textbook to learn or refresh core DSP techniques and their implementation in MATLAB.
Level: Intermediate — Prerequisites: Basic signals-and-systems concepts, single-variable calculus, matrix algebra (linear algebra), basic probability and random processes, and familiarity with a programming environment (MATLAB or similar).
Key Takeaways
- Implement and analyze DFT/FFT algorithms (including prime-factor and sliding-DFT variants) in software
- Design and realize FIR and IIR digital filters using window, frequency-sampling, and bilinear-transform methods
- Perform spectral analysis and power spectral density estimation using nonparametric and parametric techniques
- Apply short-time Fourier transform and wavelet methods for time-frequency analysis of audio and nonstationary signals
- Develop and test adaptive filters (e.g., LMS variants) and understand their convergence and tracking behavior
- Translate DSP theory into practical MATLAB programs and simulations for audio/speech, radar, and communications applications
Topics Covered
- Introduction and Review of Discrete-Time Signals and Systems
- Time-Domain Analysis of Discrete-Time Systems
- The z-Transform and System Function
- Discrete-Time Fourier Transform (DTFT) and Properties
- Sampling and Discrete-Time Representation of Continuous Signals
- The Discrete Fourier Transform (DFT) and Spectral Analysis
- Fast Fourier Transform (FFT) Algorithms (including prime-factor and radix variants)
- Digital Filter Design: FIR and IIR Techniques
- Filter Realization Structures and Numerical Issues
- Multirate Signal Processing and Decimation/Interpolation
- Short-Time Characterization and Time–Frequency Methods (STFT)
- Wavelet Transforms and Multiresolution Analysis
- Adaptive Filtering and LMS-family Algorithms
- Statistical Signal Processing and Spectral Estimation
- Applications: Audio/Speech, Radar, and Communications; MATLAB Exercises
Languages, Platforms & Tools
How It Compares
Similar in coverage to Oppenheim & Schafer's Discrete-Time Signal Processing and Proakis & Manolakis's DSP texts, but Mitra emphasizes a computer-based, MATLAB-driven pedagogy with more applied examples and extensive exercises.
