NDLI: Design and simulations of cellular neural-like associative memory

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Design and simulations of cellular neural-like associative memory

Content Provider	IEEE Xplore Digital Library
Author	Bandman, O. Pudov, S.
Copyright Year	1997
Description	Author affiliation: Dept. of Supercomput. Software, Comput. Center, Novisbirsk, Russia (Bandman, O.)
Abstract	A cellular-neuron associative memory (CNAM), which is an associative neural memory of the Hopfield type with a restricted number of connections, is investigated. Algorithms for designing CNAMs take advantage of the fine-grained parallelism induced both by independent cell operations and by connection locality. A very important property is the fact that learning and retrieval processes may be performed in the same cellular array. Some necessary and sufficient conditions for strong stability and k-attractability are obtained, which are expressed in terms of cell neighborhood relations of stored patterns. Simulation of learning and retrieval processes in a CNAM storing symbols drawn in thin lines showed that, for this class of patterns, it is possible to provide strong stability approximately for 2\|Q\| prototypes, where Q is the cardinality of the neuron neigborhood, with the capability of restoring 60-70% of 1-distortions.
Starting Page	49
Ending Page	56
File Size	729796
Page Count	8
File Format	PDF
ISBN	0818677732
DOI	10.1109/IDSRTA.1997.568657
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-01-09
Publisher Place	Israel
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Associative memory Neurons Computational modeling Parallel processing Automata Stability Image restoration Computer networks Concurrent computing Optical computing
Content Type	Text
Resource Type	Article

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