On the complete stability of nonsymmetric cellular neural networks

Norikazu Takahashi; Leon O. Chua

doi:10.1109/81.703843

On the complete stability of nonsymmetric cellular neural networks

Norikazu Takahashi, Leon O. Chua

Research output: Contribution to journal › Article › peer-review

62 Citations (Scopus)

Abstract

This paper gives a new sufficient condition for complete stability of a nonsymmetric cellular neural network (CNN). The convergence theorem of the Gauss-Seidel method, which is an iterative technique for solving a linear algebraic equation, plays an important role in our proof. It is also shown that the existence of a stable equilibrium point does not imply complete stability of a nonsymmetric CNN.

Original language	English
Pages (from-to)	754-758
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume	45
Issue number	7
DOIs	https://doi.org/10.1109/81.703843
Publication status	Published - 1998
Externally published	Yes

Keywords

Cellular neural networks
Complete stability
Gaussseidel method

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/81.703843

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