A fast fixed point learning method to implement associative memory on cnn's

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Abstract

Cellular Neural Networks (CNN's) with space-varying inter-connections are considered here to implement associative memories. A fast learning method is presented to compute the interconnection weights. The algorithm was carefully tested and compared to other methods. Storage capacity, noise immunity, and spurious state avoidance capability of the proposed system are discussed.

Original languageEnglish
Pages (from-to)362-366
Number of pages5
JournalIEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume44
Issue number4
DOIs
Publication statusPublished - Dec 1 1997

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Keywords

  • Associative memory
  • Fixed point

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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