Backpropagation: Theory, Architectures, and Applications - Rilegato

Rilegato

ISBN 10: 080581258X ISBN 13: 9780805812589

Casa editrice: Psychology Press, 1995

Riassunto

Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.

Su questo libro

Informazioni sull?autore

Yves Chauvin, David E. Rumelhart

Dettagli dell'edizione

• Editore: Psychology Press
• Data di pubblicazione: 1995
• Lingua: Inglese
• ISBN 10: 080581258X
• ISBN 13: 9780805812589
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 574
• Redattore: Chauvin Yves, Rumelhart David E.
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile