Mathematics of Neural Networks
Subtitle: Models, Algorithms and Applications
By: edited by Stephen W. Ellacott, John C. Mason, Iain J. Anderson
Contributors: Mason, John C.; Anderson, Iain J.
Series: Operations Research/Computer Science Interfaces Series -- 8; Operations research/computer science interfaces series -- 8.
Publisher: Springer US
Published: 1997
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 403
ISBN-13: 9781461377948; 9781461560999
Subjects: Artificial intelligence; Mathematical optimization; Computer science; Operations research
Description: This book examines the mathematics, probability, statistics, and computational theory underlying neural networks and their applications. In addition to the theoretical work, the book covers a considerable range of neural network topics such as learning and training, neural network classifiers, memory-based networks, self-organizing maps and unsupervised learning, Hopfeld networks, radial basis function networks, and general network modelling and theory. Added to the book's mathematical and neural network topics are applications in chemistry, speech recognition, automatic control, nonlinear programming, medicine, image processing, finance, time series, and dynamics. As a result, the book surveys a wide range of recent research on the theoretical foundations of creating neural network models in a variety of application areas.
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