An Introduction to Identification

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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 identification algorithms and their applications. Numerical examples show how to apply modeling theories. 1986 edition.

Audience: Control engineers, researchers, ...

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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 identification algorithms and their applications. Numerical examples show how to apply modeling theories. 1986 edition.

Audience: Control engineers, researchers, students, and systems engineers.

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Product Details

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.
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