Random iterative models
By: Marie Duflo ; translated by Stephen S. Wilson.
Series: Applications of mathematics,; 34
Publisher: Springer
Published: 1997
Place of publication: Berlin; New York
Language: eng
Number of pages: 385
Subjects: Iterative methods (Mathematics); Stochastic processes; Adaptive control systems -- Mathematical models
Description: The recent development of computation and automation has led to quick advances in the theory and practice of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, organizing multi-access broadcast channels, self-learning of neural networks...). This book provides a wide-angle view of those methods: stochastic approximation, linear and non-linear models, controlled Markov chains, estimation and adaptive control, learning...

Mathematicians familiar with the basics of Probability and Statistics will find here a self-contained account of many approaches to those theories, some of them classical, some of them leading up to current and future research. Each chapter can form the core material for lectures on stochastic processes. Engineers having to control complex systems will find here algorithms with good performances and reasonably easy computation.
Notes: Includes bibliographical references (p. [349]-379) and index.