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Random Processes for Engineers - A Primer (Paperback)
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Random Processes for Engineers - A Primer (Paperback)
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This book offers an intuitive approach to random processes and
educates the reader on how to interpret and predict their behavior.
Premised on the idea that new techniques are best introduced by
specific, low-dimensional examples, the mathematical exposition is
easier to comprehend and more enjoyable, and it motivates the
subsequent generalizations. It distinguishes between the science of
extracting statistical information from raw data--e.g., a time
series about which nothing is known a priori--and that of analyzing
specific statistical models, such as Bernoulli trials, Poisson
queues, ARMA, and Markov processes. The former motivates the
concepts of statistical spectral analysis (such as the
Wiener-Khintchine theory), and the latter applies and interprets
them in specific physical contexts. The formidable Kalman filter is
introduced in a simple scalar context, where its basic strategy is
transparent, and gradually extended to the full-blown iterative
matrix form.
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