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An introduction to neural networks
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An introduction to neural networks

Author: James A Anderson; M.I.T. Press.
Publisher: Cambridge, Mass. : MIT Press, ©1995.
Edition/Format: eBook : Document : EnglishView all editions and formats
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James A Anderson; M.I.T. Press.
ISBN: 0262510812 9780262510813
OCLC Number: 62108875
Notes: Title from title screen (viewed October 12, 2005)
Details: Mode of access: World Wide Web.
Contents: Introduction -- Acknowledgements -- 1. Properties of Single Neurons -- 2. Synaptic Integration and Neuron Models -- 3. Essential Vector Operations -- 4. Lateral Inhibition and Sensory Processing -- 5. Simple Matrix Operations -- 6. The Linear Associator: Background and Foundations -- 7. The Kinear Associator: Simulations -- 8. Early Network Models: The Perceptron -- 9. Gradient Descent Algorithms -- 10. Representation of Information -- 11. Applications of Simple Associators: Concept Formation and Object Motion -- 12. Energy and Neural Networks: Hopfield Networks and Boltzmann Machines -- 13. Nearest Neighbor Models -- 14. Adaptive Maps -- 15. The BSB Model: A Simple Nonlinear Autoassociative Neural Network -- 16. Associative Computation -- 17. Teaching Arithmetic to a Neural Network -- Afterword -- Index.
Other Titles: MIT CogNet.
Responsibility: James A. Anderson.

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