Random Iterative Models: 34 - Rilegato

Duflo, Marie

Rilegato

ISBN 10: 3540571000 ISBN 13: 9783540571001

Casa editrice: Springer Nature, 1996

Riassunto

An up-to-date, self-contained review of a wide range 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 ...). Suitable for mathematicians (researchers and also students) and engineers.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 1996
• Lingua: Inglese
• ISBN 10: 3540571000
• ISBN 13: 9783540571001
• Rilegatura: Copertina rigida
• Numero di pagine: 385
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania