Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays

Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays

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 f...

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Main Authors: J. Thipcha, P. Niamsup
Format: Journal
Published: 2018
Subjects:
Mathematics
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84879318346&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/52751
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-527512018-09-04T09:31:32Z Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays J. Thipcha P. Niamsup Mathematics 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. © 2013 J. Thipcha and P. Niamsup. 2018-09-04T09:31:32Z 2018-09-04T09:31:32Z 2013-06-28 Journal 16870409 10853375 2-s2.0-84879318346 10.1155/2013/576721 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84879318346&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/52751
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Mathematics
spellingShingle Mathematics
J. Thipcha
P. Niamsup
Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
description 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. © 2013 J. Thipcha and P. Niamsup.
format Journal
author J. Thipcha
P. Niamsup
author_facet J. Thipcha
P. Niamsup
author_sort J. Thipcha
title Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
title_short Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
title_full Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
title_fullStr Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
title_full_unstemmed Global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
title_sort global exponential stability criteria for bidirectional associative memory neural networks with time-varying delays
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84879318346&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/52751
_version_ 1681424008281587712

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