Neural Networks: A Systematic Introduction

Rojas, Raul

ISBN 10: 3540605053 / ISBN 13: 9783540605058

Published by Springer Verlag, 1996

About this Item

1st edition. 522 pages. German language. 9.50x6.25x1.25 inches. In Stock.

Seller Inventory # x-3540605053

Bibliographic Details

• Title: Neural Networks: A Systematic Introduction
• Publisher: Springer Verlag
• Publication Date: 1996
• Language: English
• ISBN 10: 3540605053
• ISBN 13: 9783540605058
• Binding: Paperback
• Condition: Brand New
• Weight: 0.78 kilograms

About this title

Synopsis

Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

From the Back Cover

Artificial neural networks are an alternative computational paradigm with roots in neurobiology which has attracted increasing interest in recent years. This book is a comprehensive introduction to the topic that stresses the systematic development of the underlying theory. Starting from simple threshold elements, more advanced topics are introduced, such as multilayer networks, efficient learning methods, recurrent networks, and self-organization. The various branches of neural network theory are interrelated closely and quite often unexpectedly, so the chapters treat the underlying connection between neural models and offer a unified view of the current state of research in the field.
The book has been written for anyone interested in understanding artificial neural networks or in learning more about them. The only mathematical tools needed are those learned during the first two years at university. The text contains more than 300 figures to stimulate the intuition of the reader and to illustrate the kinds of computation performed by neural networks. Material from the book has been used successfully for courses in Germany, Austria and the United States.