Gain-Scheduled Finite-Time Synchronization for Reaction-Diffusion Memristive Neural Networks Subject to Inconsistent Markov Chains
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Xiaona | - |
dc.contributor.author | Man, Jingtao | - |
dc.contributor.author | Song, Shuai | - |
dc.contributor.author | Ahn, Choon Ki | - |
dc.date.accessioned | 2021-11-17T11:41:03Z | - |
dc.date.available | 2021-11-17T11:41:03Z | - |
dc.date.created | 2021-08-30 | - |
dc.date.issued | 2021-07 | - |
dc.identifier.issn | 2162-237X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/127751 | - |
dc.description.abstract | An innovative class of drive-response systems that are composed of Markovian reaction-diffusion memristive neural networks, where the drive and response systems follow inconsistent Markov chains, is proposed in this article. For this kind of nonlinear parameter-varying systems, a suitable gain-scheduled controller that involves a mode and memristor-dependent item is designed, so that the error system is bounded within a finite-time interval. Moreover, by constructing a novel Lyapunov-Krasovskii functional and employing the canonical Bessel-Legendre inequality and free-weighting matrix method, the conservatism of the finite-time synchronization criterion can be greatly reduced. Finally, two numerical examples are provided to illustrate the feasibility and practicability of the obtained results. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | NONLINEAR-SYSTEMS | - |
dc.subject | INTERMITTENT CONTROL | - |
dc.subject | PASSIVITY ANALYSIS | - |
dc.subject | VARYING DELAYS | - |
dc.subject | STABILITY | - |
dc.subject | CONSENSUS | - |
dc.title | Gain-Scheduled Finite-Time Synchronization for Reaction-Diffusion Memristive Neural Networks Subject to Inconsistent Markov Chains | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Ahn, Choon Ki | - |
dc.identifier.doi | 10.1109/TNNLS.2020.3009081 | - |
dc.identifier.scopusid | 2-s2.0-85093660572 | - |
dc.identifier.wosid | 000670541500013 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, v.32, no.7, pp.2952 - 2964 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | - |
dc.citation.title | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | - |
dc.citation.volume | 32 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 2952 | - |
dc.citation.endPage | 2964 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Hardware & Architecture | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | NONLINEAR-SYSTEMS | - |
dc.subject.keywordPlus | INTERMITTENT CONTROL | - |
dc.subject.keywordPlus | PASSIVITY ANALYSIS | - |
dc.subject.keywordPlus | VARYING DELAYS | - |
dc.subject.keywordPlus | STABILITY | - |
dc.subject.keywordPlus | CONSENSUS | - |
dc.subject.keywordAuthor | Markov processes | - |
dc.subject.keywordAuthor | Synchronization | - |
dc.subject.keywordAuthor | Artificial neural networks | - |
dc.subject.keywordAuthor | Memristors | - |
dc.subject.keywordAuthor | Learning systems | - |
dc.subject.keywordAuthor | Nonhomogeneous media | - |
dc.subject.keywordAuthor | Canonical Bessel-Legendre (B-L) inequality | - |
dc.subject.keywordAuthor | finite-time synchronization | - |
dc.subject.keywordAuthor | gain-scheduled controller | - |
dc.subject.keywordAuthor | inconsistent Markov chains | - |
dc.subject.keywordAuthor | Markovian reaction-diffusion memristive neural networks (MNNs) | - |
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