Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition)

Presents the fundamentals of discrete-time signals, systems, and modern digital processing algorithms and applications for students in electrical engineering, computer engineering, and computer science. Textbook. DLC: Signal processing - Digital techniques.

Giving the reader a sound balance of theory and practical application, this no-nonsense book presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications. Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it furthers the understanding with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout.

FEATURES:

• NEW—reorganizes coverage of DFT and FFT algorithm for greater clarity—now introduces the DFT and describes its efficient computation immediately following the treatment of Fourier analysis.
• Describes the operations and techniques involved in the analog-to-digital conversion of analog signals.
• Studies the characterization and analysis of linear time-invariant discrete-time systems and discrete- time signals in the time domain.
• Considers both the bilateral and the unilateral z-transform, and describes methods for determining the inverse z-transform.
• Analyzes signals and systems in the frequency domain, and presents Fourier series and Fourier transform in both continuous-time and discrete-time signals.
• Treats the realization of IIR and FIR systems, including direct-form, cascade, parallel, lattice and lattice-ladder realizations.
• Looks at the basics of sampling rate conversion and presents systems for implementing multirate conversion.
• Offers a detailed examination of power spectrum estimation, with discussions on nonparametric and model-based methods, as well as eigen-decomposition- based methods, including MUSIC and ESPRIT.
• Includes many examples throughout the book and with approximately 500 workable problems.