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Introduction To Random Processes

Description

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.

Keywords

Probability Variables Density Expectation Correlation Random processes Autocorrelation Gaussian Markov Stationary Wiener Poisson Calculus Ergodicity Duality Spectral Density Modulation Demodulation Cycloergodicity Filtering Estimation

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