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Advanced Mathematical Tools for Automatic Control Engineers: Volume 2. Stochastic Systems

  • ID: 1752604
  • Book
  • September 2009
  • Elsevier Science and Technology

Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers.

The book is divided into four main parts. Part I discusses the fundamentals of probability theory, covering probability spaces, random variables, mathematical expectation, inequalities, and characteristic functions. Part II addresses discrete time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic processes, namely Markov processes, stochastic integrals, and stochastic differential equations. Part IV presents applications of stochastic techniques for dynamic models and filtering, prediction, and smoothing problems. It also discusses the stochastic approximation method and the robust stochastic maximum principle.

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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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Alexander S. Poznyak Professor and Department Head of Automatic Control, CINESTAV of IPN, Mexico.

Alexander Poznyak is Professor and Department Head of Automatic Control at CINESTAV of IPN in Mexico. He graduated from Moscow Physical Technical Institute in 1970, and earned Ph.D. and Doctoral Degrees from the Institute of Control Sciences of Russian Academy of Sciences in 1978 and 1989, respectively. He has directed 43 Ph.D. theses, and published more than 260 papers and 14 books.
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