An improvement of the design method of cellular neural networks based on generalized eigenvalue minimization

Ryoma Bise; Norikazu Takahashi; Tetsuo Nishi

doi:10.1109/TCSI.2003.819827

An improvement of the design method of cellular neural networks based on generalized eigenvalue minimization

Ryoma Bise, Norikazu Takahashi, Tetsuo Nishi

Research output: Contribution to journal › Article

7 Citations (Scopus)

Abstract

Realization of associative memories by cellular neural networks (CNNs) with binary output is studied. Concerning this problem, a CNN design method based upon generalized eigenvalue minimization (GEVM) has recently been proposed. In this brief, a new CNN design method which is based on the GEVM-based method will be presented. We first give some analytical results related to the basin of attraction of a memory vector. We then derive the design method by combining these analytical results and the GEVM-based method. We finally show through computer simulations that the proposed method can achieve higher recall probability than the original GEVM-based method.

Original language	English
Pages (from-to)	1569-1574
Number of pages	6
Journal	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume	50
Issue number	12
DOIs	https://doi.org/10.1109/TCSI.2003.819827
Publication status	Published - Dec 1 2003
Externally published	Yes

Keywords

Associative memory
Basin of attraction
Cellular neural networks (CNNs)
Generalized eigenvalue minimization (GEVM)

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/TCSI.2003.819827

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Bise, R., Takahashi, N., & Nishi, T. (2003). An improvement of the design method of cellular neural networks based on generalized eigenvalue minimization. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 50(12), 1569-1574. https://doi.org/10.1109/TCSI.2003.819827

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