Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70717
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dc.contributor.authorUsa Humphriesen_US
dc.contributor.authorGrienggrai Rajchakiten_US
dc.contributor.authorPramet Kaewmesrien_US
dc.contributor.authorPharunyou Chanthornen_US
dc.contributor.authorRamalingam Sriramanen_US
dc.contributor.authorRajendran Samiduraien_US
dc.contributor.authorChee Peng Limen_US
dc.date.accessioned2020-10-14T08:39:52Z-
dc.date.available2020-10-14T08:39:52Z-
dc.date.issued2020-05-01en_US
dc.identifier.issn22277390en_US
dc.identifier.other2-s2.0-85085652138en_US
dc.identifier.other10.3390/MATH8050801en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85085652138&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/70717-
dc.description.abstract© 2020 by the authors. We study the global asymptotic stability problem with respect to the fractional-order quaternion-valued bidirectional associative memory neural network (FQVBAMNN) models in this paper. Whether the real and imaginary parts of quaternion-valued activation functions are expressed implicitly or explicitly, they are considered to meet the global Lipschitz condition in the quaternion field. New sufficient conditions are derived by applying the principle of homeomorphism, Lyapunov fractional-order method and linear matrix inequality (LMI) approach for the two cases of activation functions. The results confirm the existence, uniqueness and global asymptotic stability of the system's equilibrium point. Finally, two numerical examples with their simulation results are provided to show the effectiveness of the obtained results.en_US
dc.subjectMathematicsen_US
dc.titleGlobal stability analysis of fractional-order quaternion-valued bidirectional associative memory neural networksen_US
dc.typeJournalen_US
article.title.sourcetitleMathematicsen_US
article.volume8en_US
article.stream.affiliationsThiruvalluvar Universityen_US
article.stream.affiliationsVel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering Collegeen_US
article.stream.affiliationsDeakin Universityen_US
article.stream.affiliationsMaejo Universityen_US
article.stream.affiliationsKing Mongkut s University of Technology Thonburien_US
article.stream.affiliationsChiang Mai Universityen_US
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