Items related to Knowledge-Based Neurocomputing
Synopsis
Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.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,...
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.
Review
Zurada's first volume is arguable the best neural network text ever written. Cloete and Zurada's Knowledge-Based Neurocomputing continues in this tradition of excellence. Clearly and precisely written, this volume belongs in the library of every neuro smith.―Robert J. Marks II, Department of Electrical Engineering, University of Washington, Seattle, and former Editor-in-Chief, IEEE Transaction on Neural Networks
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- PublisherMit Pr
- Publication date2000
- ISBN 10 0262032740
- ISBN 13 9780262032742
- BindingHardcover
- LanguageEnglish
- Number of pages500
- EditorCloete Ian, Zurada Jacek M.
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