Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of tried-and-true identification algorithms and their applications. Moreover, its broad view and fairly modest mathematical level offer readers a quick appraisal of established methods and their limitations.
In addition to surveys covering classical methods of identification — including impulse, step, and sine-wave testing — and identification based on correlation function, the text examines least-squares model fitting, statistical properties of estimators, optimal estimation, and Bayes and maximum-likelihood estimators. Other topics include experiment design and choice of model structure as well as model validation. Numerical examples show students how to apply the modeling theories, and a chapter on specialized topics introduces research areas.
This book title, An Introduction to Identification, ISBN: 9780486469355, by J. P. Norton, published by Dover Publications (April 23, 2009) is available in paperback. Our minimum order quantity is 25 copies. All standard bulk book orders ship FREE in the continental USA and delivered in 4-10 business days.
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