Global robust exponential stability analysis for interval neural networks with mixed delays
type: Item
instance of: scholarly article
title: Global robust exponential stability analysis for interval neural networks with mixed delays
zbMATH Open document ID: 1256.93079
DOI: 10.1155/2012/647231
author: Yanke Du
author: Rui Xu
published in: Abstract and Applied Analysis
publication date: 2013-02-04T00:00:00Z
review text: Summary: A class of interval neural networks with time-varying delays and distributed delays is investigated. By employing \(H\)-matrix and \(M\)-matrix theory, homeomorphism techniques, the Lyapunov functional method, and the linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point to the neural networks are established and some previously published results are improved and generalized. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.
Mathematics Subject Classification ID: 93D09
Mathematics Subject Classification ID: 34K35
Mathematics Subject Classification ID: 34K20
zbMATH DE Number: 6134138
Wikidata QID: Q58695779
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/647231
OpenAlex ID: W2000517102
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description: scientific article; zbMATH DE number 6134138