Stochastic Models of Neural Networks

Turchetti, Claudio|Turchetti, C.

ISBN 10: 1586033883 / ISBN 13: 9781586033880

Editore: IOS Press, 2004

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks, that is networks able to learn random processes from experience, on the basis of recent developments on this subject.KlappentextrnrnTh. Codice articolo 448126157

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Titolo: Stochastic Models of Neural Networks

Casa editrice: IOS Press

Data di pubblicazione: 2004

Legatura: Rilegato

Condizione: New

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Riassunto:

Turchetti (Universita Politecnica delle Marche) investigates the properties of neural networks as sources of random functions, and whether approximating properties similar to those valid for deterministic functions hold for random functions. After introducing the mathematical model of artificial neural networks, he describes some fundamental results of the stochastic process theory, examines the space of functions generated by stochastic neural networks, and defines architectures for the implementation of stochastic networks. The final chapter considers the process of modeling and memorizing physical events as stochastic processes, and approaches the problem of neural computing from a different angle than digital computers. Annotation ©2005 Book News, Inc., Portland, OR (booknews.com)

Dal risvolto di copertina interno:

This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks,that is networks able to learn random processes from experience, on the basis of recent developments on this subject. The mathematical frameworks on which the theory is founded embrace the approximation of non-random functions as well as the theory of stochastic processes. The networks so defined constitute an original and very promising model of human brain neural activity consistent with the need of learning from a stochastic environment. Moreover, the problem of speech modeling, both for synthesis and recognition, is faced as concrete and significant application in the field of artificial intelligence of the theory is presented.