Discrete Mathematics of Neural Networks
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Discrete Mathematics of Neural Networks by Martin Anthony
Book DescriptionThis concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.
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Book DetailsISBN: 9780898714807
(228mm x 152mm x 12mm)
Imprint: Society for Industrial & Applied Mathematics,U.S.
Publisher: Society for Industrial & Applied Mathematics,U.S.
Publish Date: 1-Jan-1987
Country of Publication: United States
Books By Author Martin Anthony
Linear Algebra: Concepts and Methods, Paperback (May 2012)
This thorough, yet concise, treatment of all the key topics also gives students a sound understanding of the underlying theory.
Neural Network Learning, Paperback (August 2009)
This book describes theoretical advances in the study of artificial neural networks.
Mathematics for Economics and Finance, Paperback (July 1996)» View all books by Martin Anthony
An introduction to mathematical modelling in economics and finance.
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