A new methodology to the design of associative memories based on cellular neural networks

Hye Yeon Kim, Jooyoung Park, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this paper, we consider the problem of realizing associative memories via cellular neural networks(CNNs). We formulate the synthesis of CNN that can store given binary vectors with improved performance as a constrained optimization problem. Next, we convert the synthesis problem into a generalized eigenvalue problem(GEVP), which can be efficiently solved by recently developed interior point methods. The validity of the proposed approach is illustrated by computer simulations.

Original languageEnglish
Pages (from-to)965-968
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume15
Issue number2
Publication statusPublished - 2000

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'A new methodology to the design of associative memories based on cellular neural networks'. Together they form a unique fingerprint.

Cite this