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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Main Authors: | |
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Corporate Authors: | |
Published: |
Elsevier Science,
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Publisher Address: | Amsterdam ; Boston : |
Publication Dates: | 2009. |
Literature type: | eBook |
Language: | English |
Edition: | First edition. |
Subjects: | |
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 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. |
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. |