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Neural network learning and expert systems [electronic resource] / Stephen I. Gallant.

By: Gallant, Stephen I.
Material type: TextTextPublisher: Cambridge, Mass. : MIT Press, c1993Description: 1 online resource (xvi, 365 p.) : ill.ISBN: 0585040281 (electronic bk.); 9780585040288 (electronic bk.); 0262071452; 9780262071451; 9780262273404 (electronic bk.); 0262273403 (electronic bk.).Subject(s): Neural networks (Computer science) | Expert systems (Computer science) | COMPUTERS -- Enterprise Applications -- Business Intelligence Tools | COMPUTERS -- Intelligence (AI) & Semantics | Inteligencia Artificial | back propagation | apprentissage | systeme expert | reseau neuronal | Syst�emes experts (informatique) | R�eseaux neuronaux (informatique) | Intelligence artificielleGenre/Form: Electronic books.Additional physical formats: Print version:: Neural network learning and expert systems.DDC classification: 006.3 Online resources: EBSCOhost
Contents:
Introduction and important definitions -- Representation issues -- Perceptron learning and the pocket algorithm -- Winner-take-all groups or linear machines -- Autoassociators and one-shot learning -- Mean squared error (MSE) algorithms -- Unsupervised learning -- The distributed method and radial basis functions -- Computational learning theory and the BRD algorithm -- Constructive algorithms -- Backpropagation -- Backpropagation : variations and applications -- Simulated annealing and boltzmann machines -- Expert systems and neural networks -- Details of the MACIE system -- Noise, redundancy, fault detection, and bayesian decision theory -- Extracting rules from networks.
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"A Bradford Book."

Includes bibliographical references (p. [349]-359) and index.

Description based on print version record.

1. Introduction and important definitions -- 2. Representation issues -- 3. Perceptron learning and the pocket algorithm -- 4. Winner-take-all groups or linear machines -- 5. Autoassociators and one-shot learning -- 6. Mean squared error (MSE) algorithms -- 7. Unsupervised learning -- 8. The distributed method and radial basis functions -- 9. Computational learning theory and the BRD algorithm -- 10. Constructive algorithms -- 11. Backpropagation -- 12. Backpropagation : variations and applications -- 13. Simulated annealing and boltzmann machines -- 14. Expert systems and neural networks -- 15. Details of the MACIE system -- 16. Noise, redundancy, fault detection, and bayesian decision theory -- 17. Extracting rules from networks.

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Neural network learning and expert systems by Gallant, Stephen I. ©1993
Neural network learning and expert systems by Gallant, Stephen I. ©1993
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