Adaptive Filtering Prediction and Control (Dover Books on Electrical Engineering)

Table of Contents:
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary of Some Stability ResultsC. Passive Systems TheoryD. Probability Theory and Stochastic ProcessesE. Matrix Riccati EquationsReferencesIndex

Marc Notes:
Originally published: Englewood Cliffs, N.J.: Prentice Hall, 1984.;Includes bibliographical references (p. 516-534) and index.

Biographical Note:
Graham C. Goodwin is Laureate Professor of Electrical Engineering at the University of Newcastle, Australia. Kwai Sang Sin is also affiliated with the Department of Electrical Engineering at the University of Newcastle.

Publisher Marketing:
This unified survey of the theory of adaptive filtering, prediction, and control focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems. In keeping with the importance of computers to practical applications, the authors emphasize discrete-time systems. Their approach summarizes the theoretical and practical aspects of a large class of adaptive algorithms.
Ideal for advanced undergraduate and graduate classes, this treatment consists of two parts. The first section concerns deterministic systems, covering models, parameter estimation, and adaptive prediction and control. The second part examines stochastic systems, exploring optimal filtering and prediction, parameter estimation, adaptive filtering and prediction, and adaptive control. Extensive appendices offer a summary of relevant background material, making this volume largely self-contained. Readers will find that these theories, formulas, and applications are related to a variety of fields, including biotechnology, aerospace engineering, computer sciences, and electrical engineering.