Synchronization for an array of coupled Cohen-Grossberg neural networks with time-varying delay
type: Item
instance of: scholarly article
title: Synchronization for an array of coupled Cohen-Grossberg neural networks with time-varying delay
zbMATH Open document ID: 1213.93110
DOI: 10.1155/2011/831695
author: Hai-Tao Zhang
author: Tao Li
author: Shumin Fei
published in: Mathematical Problems in Engineering
publication date: 2011-06-07T00:00:00Z
full work available at URL: https://eudml.org/doc/233249
review text: Summary: This paper makes some great attempts to investigate the global exponential synchronization for arrays of coupled delayed Cohen-Grossberg neural networks with both delayed coupling and one single delayed one. By resorting to free-weighting matrix and Kronecker product techniques, two novel synchronization criteria via linear matrix inequalities (LMIs) are presented based on convex combination, in which these conditions are heavily dependent on the bounds of both the delay and its derivative. Owing to that the addressed system can include some famous neural network models as the special cases, the proposed methods can extend and improve those earlier reported ones. The efficiency and applicability of the presented conditions can be demonstrated by two numerical examples with simulations.
Mathematics Subject Classification ID: 93C40
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 5904921
Wikidata QID: Q58693570
MaRDI profile type: Publication
OpenAlex ID: W2084768404
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description: scientific article; zbMATH DE number 5904921