ENGLISH

Random Iterative Models

By Marie Duflo (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
1997
ISBN
978-3-642-08175-0, 978-3-662-12880-0
DOI
10.1007/978-3-662-12880-0
Language
english
Format
PDF
Filesize
12 MB (13042194 bytes)
Series
Stochastic Modelling and Applied Probability 34
Edition
1
Pages
385\393
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Probability Theory and Stochastic Processes; Algor

Description

The recent development of computation and automation has lead 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, orgainizing multiaccess 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 a course of lectures. Engineers having to control complex systems can discover new algorithms with good performances and reasonably easy computation.

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