Digital Signal Processing Using Matlab : A Problem Solving Companion, 4Th Edition [Paperback] Vinay K. Ingle | John G. P
Please Read Notes: Brand New, International Softcover Edition, Printed in black and white pages, minor self wear on the cover or pages, Sale restriction may be printed on the book, but Book name, contents, and author are exactly same as Hardcover Edition. Fast delivery through DHL/FedEx express.
Why Read This Book
You will get a hands-on, MATLAB-driven companion that turns DSP theory into working code and solved problems, so you can quickly prototype, visualize, and validate algorithms. The book emphasizes practical techniques across filters, FFT/spectral methods, wavelets, adaptive filtering, and real-world audio, radar and communications examples.
Who Will Benefit
Graduate and senior undergraduate engineering students, and practicing engineers who know basic signals & systems and want a MATLAB-focused, problem-solving guide to implement and test common DSP algorithms.
Level: Intermediate — Prerequisites: Undergraduate-level signals & systems (discrete-time signals, transforms), basic calculus and linear algebra, and introductory familiarity with MATLAB (or GNU Octave).
Key Takeaways
- Implement common DSP algorithms in MATLAB, including DFT/FFT routines and spectral estimation workflows.
- Design and evaluate FIR and IIR digital filters using practical design methods and filter structures.
- Apply time-frequency and wavelet analysis to real signals, and interpret scalograms and spectrograms.
- Develop and test adaptive filters (e.g., LMS, RLS) and use them for noise cancellation and system identification.
- Perform statistical signal-processing tasks such as estimation, detection, and modeling for communication and radar signals.
Topics Covered
- Introduction and MATLAB Essentials for DSP
- Discrete-Time Signals and Systems — Modeling and Simulation
- Z-Transform and System Analysis
- The Discrete Fourier Transform and Efficient FFT Algorithms
- Spectral Analysis and Modern Estimation Methods
- FIR Filter Design and Implementation
- IIR Filter Design and Realization Structures
- Multirate Signal Processing and Decimation/Interpolation
- Wavelet Transforms and Time–Frequency Methods
- Adaptive Filtering: LMS, RLS and Applications
- Statistical Signal Processing: Estimation and Detection
- Applications: Audio and Speech Processing
- Applications: Radar and Communication Signal Processing
- Appendices: MATLAB Scripts, Sample Data and Numerical Tips
Languages, Platforms & Tools
How It Compares
Unlike the theory-heavy Proakis & Manolakis or Oppenheim & Schafer, this companion focuses on MATLAB implementations and problem solutions, similar in practicality to Lyons' 'Understanding Digital Signal Processing' but with more structured worked problems and MATLAB code.
