Learning of associative memory in form of neural network suitabl

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395 22, G06F 1518

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055241778

ABSTRACT:
The learning of an associative memory suitable for the connectionist model which can deal with the patterns having the non-random frequencies of the appearances or the non-random correlations. In this invention, the learning of the associative memory in a form of a neural network, in which a plurality of nodes having activation values are connected by a plurality of links having link weight values, is achieved by entering a plurality of learning patterns sequentially, where each learning pattern has a plurality of elements in correspondence with the nodes, calculating an energy E of the entered learning pattern, determining a learning amount .delta. for the entered learning pattern according to a difference between the calculated energy E and a predetermined reference energy level Eth, and updating the link weight values of the links according to the entered learning pattern and the determined learning amount .delta..

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