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Random Iterative Models /
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...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
1997.
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| Colección: | Stochastic modelling and applied probability ;
34. |
| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | 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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| Descripción Física: | 1 online resource (xv, 387 pages) |
| ISBN: | 9783662128800 3662128802 |
| ISSN: | 0172-4568 ; |