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

Author: Alexander S Poznyak
Publisher: Amsterdam ; Boston : Elsevier Science, 2009.
Edition/Format:   eBook : Document : English : 1st edView all editions and formats
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Poznyak, Alexander S.
Advanced mathematical tools for automatic control engineers.
Oxford : Elsevier Science, 2009
Volume 2, Stochastic techniques.
(OCoLC)319208894
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Alexander S Poznyak
ISBN: 9780080914039 0080914039
OCLC Number: 455361523
Description: 1 online resource (xxix, 538 pages) : illustrations
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.
Other Titles: Stochastic techniques
Responsibility: Alex Poznyak.

Abstract:

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 system and automatic control theories. It also has applications to game theory, machine learning and intelligent systems. * Provides comprehensive theory of matrices, real, complex and functional analysis * Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications * Contains worked proofs of all theorems and propositions presented.

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