Abstract

From the Publisher: This book represents the most comprehensive treatment available of neural networks from an engineering perspective. Thorough, well-organized, and completely up to date, it examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks. Written in a concise and fluid manner, by a foremost engineering textbook author, to make the material more accessible, this book is ideal for professional engineers and graduate students entering this exciting field. Computer experiments, problems, worked examples, a bibliography, photographs, and illustrations reinforce key concepts.

Keywords

Modular designComputer scienceField (mathematics)Artificial neural networkProcess (computing)Function (biology)Ideal (ethics)Key (lock)Perspective (graphical)Artificial intelligenceFoundation (evidence)EngineeringGeographyEpistemologyMathematics

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Publication Info

Year
1998
Type
book
Citations
29814
Access
Closed

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Simon Haykin (1998). Neural Networks: A Comprehensive Foundation. .