Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58495
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dc.contributor.authorJ. Thipchaen_US
dc.contributor.authorP. Niamsupen_US
dc.date.accessioned2018-09-05T04:25:35Z-
dc.date.available2018-09-05T04:25:35Z-
dc.date.issued2018-06-01en_US
dc.identifier.issn09410643en_US
dc.identifier.other2-s2.0-84996606704en_US
dc.identifier.other10.1007/s00521-016-2657-1en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84996606704&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58495-
dc.description.abstract© 2016, The Natural Computing Applications Forum. In this paper, the exponential passivity for bidirectional associative memory (BAM) neural networks with time-varying delays is considered. 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 passivity criterion for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI). A numerical example is given to show that the derived condition is less conservative than some existing results given in the literature.en_US
dc.subjectComputer Scienceen_US
dc.titleNew exponential passivity of BAM neural networks with time-varying delaysen_US
dc.typeJournalen_US
article.title.sourcetitleNeural Computing and Applicationsen_US
article.volume29en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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