Digital Signal Processing: Principles, Algorithms and Applications: International Edition, 3/e

Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms.

Giving students a sound balance of theory and practical application, this no-nonsense text 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 further prepares students with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout.

Introduction to Wavelets and Wavelet Transforms: A Primer, 1/e

Advanced undergraduate and beginning graduate students, faculty, researchers and practitioners in signal processing, telecommunications, and computer science, and applied mathematics. It assumes a background of Fourier series and transforms and of linear algebra and matrix methods.

This primer presents a well balanced blend of the mathematical theory underlying wavelet techniques and a discussion that gives insight into why wavelets are successful in signal analysis, compression, dection, numerical analysis, and a wide variety of other theoretical and practical applications. It fills a gap in the existing wavelet literature with its unified view of expansions of signals into bases and frames, as well as the use of filter banks as descriptions and algorithms.