Random Processes for Engineers : A Primer
Arthur David Snider
Sold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
New - Soft cover
Condition: New
Quantity: 4 available
Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since August 14, 2006
Condition: New
Quantity: 4 available
Add to basketnach der Bestellung gedruckt Neuware - Printed after ordering - This book discusses the statistical description of processes, including an extensive review of probability and statistics and the analysis of raw data using spectral methods. Various theoretical models (ARMA, Bernoulli, shot, Markov, and random walks) are explored, as well as techniques that are used for prediction-least mean-squared error, Wien.
Seller Inventory # 9780367656355
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.
Dr. Arthur David Snider has over fifty years of experience in modeling physical systems in the areas of heat transfer, electromagnetics, microwave circuits, and orbital mechanics, as well as the mathematical areas of numerical analysis, signal processing, differential equations, and optimization. He holds degrees in both mathematics (BS, MIT, PhD, NYU) and physics (MA, Boston U), and he is a registered professional engineer. He served for forty-five years on the faculties of mathematics, physics, and electrical engineering at the University of South Florida after working for five years as a systems analyst at MIT's Draper Instrumentation Lab. He consults in many industries in Florida and has published five other textbooks in applied mathematics.
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