Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
type: Item
instance of: scholarly article
title: Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
zbMATH Open document ID: 1296.34158
DOI: 10.1155/2013/576721
author: J. Thipcha
author: P. Niamsup
published in: Abstract and Applied Analysis
publication date: 2014-06-23T00:00:00Z
review text: Summary: The global exponential stability for bidirectional associative memory neural networks with time-varying delays is studied. In our study, the lower and upper bounds of the activation functions are allowed to be either positive, negative, or zero. By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential stability for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI). Numerical examples are given to demonstrate that the derived condition is less conservative than some existing results given in the literature.
Mathematics Subject Classification ID: 34K20
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 6307019
zbMATH Keywords: Lyapunov-Krasovskii functional
zbMATH Keywords: linear matrix inequality
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/576721
OpenAlex ID: W1991392958
Wikidata QID: Q58917170
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description: scientific article; zbMATH DE number 6307019