| Summary: | The second volume of this work addresses stochastic systems, providing mathematical tools for the control engineer and demonstrating practical examples of modern optimization methods that can be used effectively in a variety of real-world applications. It examines such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimization, discrete martingales and probability space. Proofs are included for all theorems and propositions presented, and the book also contains many examples with solutions, making it suitable for use in advanced undergraduate or graduate level courses in mathematics for automatic control engineering and related areas. This book 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. |
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