Title :
Neural processing of information
Author_Institution :
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
fDate :
27 Jun-1 Jul 1994
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;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.394751
