Includes bibliographical references (pages 377-380) and index.
CONTENTS NOTE
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Probability theory -- Random variables and stochastic processes -- Conditional expectations and discrete-time Kalman filtering -- Least squares, the orthogonal projection Lemma, and discrete-time Kalman filtering -- Stochastic processes and stochastic calculus -- Continuous-time Guass-Markov systems -- The extended Kalman filter -- A selection of results from estimation theory -- Stochastic control and linear quadratic Guassian control problem -- Linear exponential Guassian control and estimation.
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SUMMARY OR ABSTRACT
Text of Note
"The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to H[subscript 2] and H[subscript [infinity]] controllers and system robustness." "This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful."--Jacket.