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Information-Theoretic Aspects of Neural Networks

P. S. Neelakanta




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 | #5258310 in Books |  CRC Press |  1999-03-30 | Original language:English | PDF # 1 |  9.75 x6.50 x1.00l,1.50 | File type: PDF | 416 pages

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||2 of 2 people found the following review helpful.| A good book dealing with stochastical neural networks.|By Karthik Sundaram|This book has dealt with in depth the various entropy error measures that can be used for the neural networks. The Minimum entropy error measures and the Maximum entropy error functions like the Kapur measures, Sharma-Mittal error measures are discussed as an alternative to the classical square error m

Information theoretics vis-a-vis neural networks generally embodies parametric entities and conceptual bases pertinent to memory considerations and information storage, information-theoretic based cost-functions, and neurocybernetics and self-organization. Existing studies only sparsely cover the entropy and/or cybernetic aspects of neural information.
Information-Theoretic Aspects of Neural Networks cohesively explores this burgeoning discipline, covering topics such...

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