DocumentCode
2619732
Title
Neural processing of information
Author
Fry, Robert L.
Author_Institution
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
fYear
1994
fDate
27 Jun-1 Jul 1994
Firstpage
217
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; information theory; maximum entropy methods; signal processing; Hopfield neuron model; Shannon information measures; conditionalized Hebbian learning rule; information channel; maximum entropy; mutual information; neural information processing; sigmoidal transfer characteristic; Analytical models; Biological information theory; Biological system modeling; Entropy; Equations; Hebbian theory; Mutual information; Neurons; Output feedback; Physics;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location
Trondheim
Print_ISBN
0-7803-2015-8
Type
conf
DOI
10.1109/ISIT.1994.394751
Filename
394751
Link To Document