Introduction To Random Processes
by William A. Gardner
Publisher: McGraw-Hill 1990
Number of pages: 560
Intended to serve primarily as a first course on random processes for graduate-level engineering and science students, particularly those with an interest in the analysis and design of signals and systems. This new edition includes over 350 exercises, new material on applications of cyclostationary processes, detailed coverage of minimum-mean-squared-error estimation, and much more. Includes coverage of spectral analysis, dynamical systems, and statistical signal processing.
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by J. H. Karl - Academic Press
The book comprises a one-semester or self-study course, filling the gap between several oversimplified introductions and more topically specialized or formal treatments. Karl's book wins notable points for its easy reading style.
by Sophocles J. Orfanidis - Prentice Hall
An applications-oriented introduction to digital signal processing. The author covers all the basic DSP concepts, such as sampling, DFT/FFT algorithms, etc. The book emphasizes the algorithmic, computational, and programming aspects of DSP.
by Jeff Fessler - University of Michigan
Course objectives: 1. to teach students the concepts of discrete-time signals, including mathematical representations; 2. to teach students the concepts of linear time-invariant discrete-time systems; 3. to introduce the concepts of filter design.
by William A. Gardner - Prentice Hall
This book is intended to serve as both a graduate-level textbook and a technical reference. The focus is on fundamental concepts, analytical techniques, and basic empirical methods. The only prerequisite is an introductory course on Fourier analysis.