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Author: Boltư̐iư̐anskiư̐i,V. G.

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Advanced mathematical tools for automatic control engineers. Volume 2, Stochastic techniques /

The second volume of this work continues the and approach of the first volume, providing mathematical tools for the control engineer and examining such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimizat...

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Bibliographic Details
Main Authors: Poznyak, Alexander S
Corporate Authors: Elsevier Science & Technology
Published: Elsevier Science,
Publisher Address: Amsterdam ; Boston :
Publication Dates: 2009.
Literature type: eBook
Language: English
Edition: First edition.
Subjects:
Automatic control > Mathematics
TECHNOLOGY & ENGINEERING > Automation
TECHNOLOGY & ENGINEERING > Robotics
Electronic books
Online Access: http://www.sciencedirect.com/science/book/9780080446738
Summary: The second volume of this work continues the and approach of the first volume, providing mathematical tools for the control engineer and examining such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimization, discrete martingales and probability space. It includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to
Carrier Form: 1 online resource (xxix, 538 pages) : illustrations
Bibliography: Includes bibliographical references (pages 529-533) and index.
ISBN: 9780080914039
0080914039
Index Number: TJ212
CLC: TP273
Contents: Preface; Introduction; Probability Space; Random Variables; Mathematical Expectation; Random Sequences; Conditional Mathematical Expectation; Discrete Martingales; Large Number Laws; Characteristic Functions and the Central Limit Theorem; Iterative Logarithmic Law; Stochastic Differential Equations; Wiener and Kalman Filtering; Parametric Identification under Stochastic Measurements; Stochastic Optimization; Finite Markov Chains, Discrete Events and Elements of Queering Theory.

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