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An automaton framework for neural nets that learn

โœ Scribed by William L. Kilmer; Michael A. Arbib

Book ID
104139574
Publisher
Elsevier Science
Year
1973
Weight
340 KB
Volume
5
Category
Article
ISSN
0020-7373

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โœฆ Synopsis

Brindley (1967Brindley ( , 1969

has discussed nets of several types of formal neurons, many of whose functions are modifiable by their own input stimuli. Because Brindley's results are widely referred to, for example Mart (1970Mart ( , 1971) ) and include some of the scarce non-trivial theorems on learning nets, it is important that serious side-conditions be made explicit. The language of finite automata is used to mathematicize the problem of adaptation sutficiently to remove some ambiguities of Brindley's approach. We close the paper by relating our framework to other formal studies of adaptation.

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Neural firing is herein considered to be a sequence of changes of state of the neuron. Thus, a state diagram analysis of the neuron or of neural nets would seem to be a more natural procedure to follow than would simple logic element analysis. This paper describes a theoretical analysis of the indi