DocumentCode
2345978
Title
Neural processing of information
Author
Fry, Robert L.
Author_Institution
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
fYear
1994
fDate
27-29 Oct 1994
Firstpage
88
Abstract
A model is proposed in which the neuron serves as an information channel. An application of the Shannon information measures of entropy and mutual information taken together in the context of the proposed model lead to the Hopfield neuron model with a conditionalized Hebbian learning rule and sigmoidal transfer characteristic
Keywords
Hebbian learning; Hopfield neural nets; maximum entropy methods; Hopfield neuron model; Shannon information measures; conditionalized Hebbian learning rule; information channel; information processing; maximum entropy; model; mutual information; neural processing; sigmoidal transfer characteristic; Analytical models; Biological information theory; Biological system modeling; Context modeling; Entropy; Equations; Laboratories; Mutual information; Neurons; Physics;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on
Conference_Location
Alexandria, VA
Print_ISBN
0-7803-2761-6
Type
conf
DOI
10.1109/WITS.1994.513915
Filename
513915
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