Digital Signal Processing Using MATLAB & Wavelets added for testing purpose: .
Although Digital Signal Processing (DSP) has long been considered an electrical engineering topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware circles. Designed for upper division engineering and computer science students as well as practicing engineers and scientists, Digital Signal Processing Using MATLAB & Wavelets, Second Edition emphasizes the practical applications of signal processing. Over 100 MATLAB examples and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound. This Second Edition also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to MATLAB programming, it moves through filters, sinusoids, sampling, the Fourier transform, the z-transform and other key topics. Two chapters are dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies every new printed copy of the book and contains source code, projects for each chapter, and the figures from the book. (eBook version does not include the CD-ROM)
Why Read This Book
You should read this book if you want a hands-on DSP introduction that ties core theory to practical implementations in MATLAB and introduces modern wavelet techniques. It gives numerous worked MATLAB examples so you can quickly prototype filters, transforms, and wavelet analyses on audio and image data.
Who Will Benefit
Upper-division undergraduates, graduate students, and practicing engineers who need a practical DSP reference with MATLAB examples and a modern introduction to wavelets.
Level: Intermediate — Prerequisites: Basic calculus and linear algebra, an introductory course in signals and systems (discrete-time signals and linear systems), and familiarity with basic programming concepts; basic MATLAB familiarity is helpful.
Key Takeaways
- Implement and experiment with core DSP algorithms in MATLAB (DFT/FFT, convolution, filtering).
- Design and analyze FIR and IIR digital filters and evaluate their frequency responses and stability.
- Apply windowing and spectral analysis techniques to estimate and interpret power spectra.
- Use multirate concepts (decimation/interpolation) for sampling-rate conversion and subband processing.
- Perform wavelet transforms and use wavelet-based methods for signal and image analysis and denoising.
Topics Covered
- Introduction and MATLAB review / Practical MATLAB examples
- Discrete-time signals and systems / Convolution and difference equations
- Z-transform and system analysis
- Sampling and reconstruction / A/D and D/A basics
- DFT and FFT algorithms
- Spectral analysis and windowing
- Digital filter design: FIR methods
- Digital filter design: IIR methods and implementation
- Multirate signal processing (decimation, interpolation, polyphase)
- Wavelet transforms: theory and discrete wavelet transform
- Wavelet applications: denoising, compression, image and audio examples
- Practical projects and extended MATLAB case studies / Appendices
Languages, Platforms & Tools
How It Compares
Less theoretical/deeper-math than Oppenheim & Schafer's Discrete-Time Signal Processing, but more application-focused and MATLAB-driven; closer in spirit to Richard Lyons' Understanding Digital Signal Processing for practitioners, with the added emphasis on wavelets.
