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Neural Network Formalization
Type of publication: Idiap-RR
Citation: fiesler-92.01
Number: Idiap-RR-01-1992
Year: 1992
Institution: IDIAP
Abstract: In order to assist the field of neural networks in its maturing, a formalization and a solid foundation are essential. Additionally, to permit the introduction of formal proofs, it is essential to have an all encompassing formal mathematical definition of a neural network. Most neural networks, even biological ones, exhibit a layered structure. This publication shows that all neural networks can be represented as layered structures. This layeredness is therefore chosen as the basis for a formal neural network framework. This publication offers a neural network formalization consisting of a topological taxonomy, a uniform nomenclature, and an accompanying consistent mnemonic notation. Supported by this formalization, both a flexible hierarchical and a universal mathematical definition are presented.
Userfields: ipdmembership={neuron learning},
Keywords: artificial neural network, connectionism, definition, formalization, mnemonic notation, neural computing, neural network statics, neurocomputing, nomenclature, standardization, terminology, topological taxonomy
Projects Idiap
Authors Fiesler, Emile
Added by: [UNK]
Total mark: 0
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