Knowledge-Based Neurocomputing

ISBN 10: 0262032740 / ISBN 13: 9780262032742

Published by MIT Press, 2000

About this Item

Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Seller Inventory # GRP62415268

Bibliographic Details

• Title: Knowledge-Based Neurocomputing
• Publisher: MIT Press
• Publication Date: 2000
• Language: English
• ISBN 10: 0262032740
• ISBN 13: 9780262032742
• Binding: Hardcover
• Edition: illustrated edition.
• Condition: Good
• Weight: 3.064 pounds

About this title

Synopsis

Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based neurocomputing, the emphasis is on the use and representation of knowledge about an application. Explicit modeling of the knowledge represented by such a system remains a major research topic. The reason is that humans find it difficult to interpret the numeric representation of a neural network.

The key assumption of knowledge-based neurocomputing is that knowledge is obtainable from, or can be represented by, a neurocomputing system in a form that humans can understand. That is, the knowledge embedded in the neurocomputing system can also be represented in a symbolic or well-structured form, such as Boolean functions, automata, rules, or other familiar ways. The focus of knowledge-based computing is on methods to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.

Contributors: C. Aldrich, J. Cervenka, I. Cloete, R.A. Cozzio, R. Drossu, J. Fletcher, C.L. Giles, F.S. Gouws, M. Hilario, M. Ishikawa, A. Lozowski, Z. Obradovic, C.W. Omlin, M. Riedmiller, P. Romero, G.P.J. Schmitz, J. Sima, A. Sperduti, M. Spott, J. Weisbrod, J.M. Zurada.

About the Author

Ian Cloete is Professor of Computer Science at the International University in Germany in Bruchsal, Germany. Jacek M. Zurada is the S. T. Fife Alumni Professor of Electrical Engineering at the University of Louisville, Louisville, Kentucky, and the Editor-in-Chief of IEEE Transactions on Neural Networks.