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Article: Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays
Title | Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays |
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Authors | |
Keywords | Fuzzy systems Hopfield neural networks Stability Stochastic systems Time-varying delay systems |
Issue Date | 2005 |
Publisher | IEEE. |
Citation | Ieee Transactions On Circuits And Systems Ii: Express Briefs, 2005, v. 52 n. 5, p. 251-255 How to Cite? |
Abstract | The ordinary Takagi-Sugeno (TS) fuzzy models have provided an approach to represent complex nonlinear systems to a set of linear sub-models by using fuzzy sets and fuzzy reasoning. In this paper, stochastic fuzzy Hopfield neural networks with time-varying delays (SFVDHNNs) are studied. The model of SFVDHNN is first establisbed as a modified TS fuzzy model in which the consequent parts are composed of a set of stochastic Hopfield neural networks with time-varying delays. Secondly, the global exponential stability in the mean square for SFVDHNN is studied by using the Lyapunov-Krasovskii approach. Stability criterion is derived in terms of linear matrix inequalities (LMIs), which can be effectively solved by some standard numerical packages. © 2005 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/43012 |
ISSN | |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
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dc.contributor.author | Huang, H | en_HK |
dc.contributor.author | Ho, DWC | en_HK |
dc.contributor.author | Lam, J | en_HK |
dc.date.accessioned | 2007-03-23T04:36:53Z | - |
dc.date.available | 2007-03-23T04:36:53Z | - |
dc.date.issued | 2005 | en_HK |
dc.identifier.citation | Ieee Transactions On Circuits And Systems Ii: Express Briefs, 2005, v. 52 n. 5, p. 251-255 | en_HK |
dc.identifier.issn | 1057-7130 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/43012 | - |
dc.description.abstract | The ordinary Takagi-Sugeno (TS) fuzzy models have provided an approach to represent complex nonlinear systems to a set of linear sub-models by using fuzzy sets and fuzzy reasoning. In this paper, stochastic fuzzy Hopfield neural networks with time-varying delays (SFVDHNNs) are studied. The model of SFVDHNN is first establisbed as a modified TS fuzzy model in which the consequent parts are composed of a set of stochastic Hopfield neural networks with time-varying delays. Secondly, the global exponential stability in the mean square for SFVDHNN is studied by using the Lyapunov-Krasovskii approach. Stability criterion is derived in terms of linear matrix inequalities (LMIs), which can be effectively solved by some standard numerical packages. © 2005 IEEE. | en_HK |
dc.format.extent | 169974 bytes | - |
dc.format.extent | 35328 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/msword | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.relation.ispartof | IEEE Transactions on Circuits and Systems II: Express Briefs | en_HK |
dc.rights | ©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Fuzzy systems | en_HK |
dc.subject | Hopfield neural networks | en_HK |
dc.subject | Stability | en_HK |
dc.subject | Stochastic systems | en_HK |
dc.subject | Time-varying delay systems | en_HK |
dc.title | Stochastic stability analysis of fuzzy Hopfield neural networks with time-varying delays | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1549-7747&volume=52&issue=5&spage=251&epage=255&date=2005&atitle=Stochastic+stability+analysis+of+fuzzy+hopfield+neural+networks+with+time-varying+delays | en_HK |
dc.identifier.email | Lam, J:james.lam@hku.hk | en_HK |
dc.identifier.authority | Lam, J=rp00133 | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/TCSII.2005.846305 | en_HK |
dc.identifier.scopus | eid_2-s2.0-20444396501 | en_HK |
dc.identifier.hkuros | 102669 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-20444396501&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 52 | en_HK |
dc.identifier.issue | 5 | en_HK |
dc.identifier.spage | 251 | en_HK |
dc.identifier.epage | 255 | en_HK |
dc.identifier.isi | WOS:000229356100005 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Huang, H=34770542600 | en_HK |
dc.identifier.scopusauthorid | Ho, DWC=7402971938 | en_HK |
dc.identifier.scopusauthorid | Lam, J=7201973414 | en_HK |
dc.identifier.issnl | 1057-7130 | - |