Second-Order Methods for Neural Networks, Adrian J. Shepherd

Автор: Brian D. Ripley
Название: Pattern Recognition and Neural Networks
ISBN: 0521717701 ISBN-13(EAN): 9780521717700
Издательство: Cambridge Academ
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Описание: This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. Valuable advice is included on both theory and applications, while case studies based on real data sets help readers develop their understanding. All data sets are available from www.stats.ox.ac.uk/~ripley/PRbook/

Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.

Автор: Okechukwu A. Uwechue; Abhijit S. Pandya
Название: Human Face Recognition Using Third-Order Synthetic Neural Networks
ISBN: 0792399579 ISBN-13(EAN): 9780792399575
Издательство: Springer
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Описание: Explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. This book serves as a reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

Автор: Eytan Domany; J. Leo van Hemmen; Klaus Schulten
Название: Models of Neural Networks III
ISBN: 0387943684 ISBN-13(EAN): 9780387943688
Издательство: Springer
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Описание: The introductory chapter, "Global Analysis of Recurrent Neural Net- works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding.

Автор: Alessandra Lintas; Stefano Rovetta; Paul F.M.J. Ve
Название: Artificial Neural Networks and Machine Learning – ICANN 2017
ISBN: 3319686119 ISBN-13(EAN): 9783319686110
Издательство: Springer
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Описание: The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions.