An Introduction to Identification

by J. P. Norton

Overview

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."

Product Details

ISBN-13:	9780486469355
Publisher:	Dover Publications
Publication date:	04/23/2009
Series:	Dover Books on Electrical Engineering Series
Pages:	320
Product dimensions:	5.30(w) x 8.40(h) x 0.80(d)

Table of Contents

Introduction. Classical Methods of Identification: Impulse, Step and Sine-Wave Testing. Identification based on Correlation Functions. Least-Squares Model Fitting. Statistical Properties of Estimators. Optimal Estimation, Bayes and Maximum-Likelihood Estimators. Computational Algorithms for Identification. Specialised Topics in Identification. Experiment Design and Choice of Model Structure. Model Validation. Each chapter includes references. Index.