Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality
This article is devoted to solving the exponential synchronization problem of a new type of fuzzy memristive neural network with reaction-diffusion terms. By introducing adaptive laws, two controllers are designed. After combining the inequality technique with the Lyapunov function approach, some ea...
Gespeichert in:
| Veröffentlicht in: | IEEE transaction on neural networks and learning systems 2024-10, Vol.35 (10), p.14825-14832 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 14832 |
|---|---|
| container_issue | 10 |
| container_start_page | 14825 |
| container_title | IEEE transaction on neural networks and learning systems |
| container_volume | 35 |
| creator | Wei, Hongzhi Li, Ruoxia |
| description | This article is devoted to solving the exponential synchronization problem of a new type of fuzzy memristive neural network with reaction-diffusion terms. By introducing adaptive laws, two controllers are designed. After combining the inequality technique with the Lyapunov function approach, some easily verified sufficient conditions are established to ensure the exponential synchronization of the reaction-diffusion fuzzy memristive system under the proposed adaptive scheme. In addition, by using the Hardy-Poincarè inequality, the diffusion terms are estimated associated with the information of the reaction-diffusion coefficients and the regional feature, which improves some existing conclusions. Finally, an illustrative example is presented to demonstrate the validity of the theoretical results. |
| doi_str_mv | 10.1109/TNNLS.2023.3281645 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_2825810929</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10149181</ieee_id><sourcerecordid>2825810929</sourcerecordid><originalsourceid>FETCH-LOGICAL-c254t-cbbd0709e8660a18573cacc1ccdb7b31ed7d53d5af5b452d20d71620fe6eb5333</originalsourceid><addsrcrecordid>eNpNkMtOwzAQRS0EAgT8AEIoSzYpfsSJww6Vp1QK4iGxixx7IgypXewESL-I_-DHSGlBzGZGM_deaQ5CuwQPCMH54f14PLobUEzZgFFB0oSvoE1KUhpTJsTq35w9bqCdEJ5xXynmaZKvow2WMYIFzTfR2-nH1FmwjZF1dNdZ9eSdNTPZGGejobONd3XkqugWpJrv4hNTVW2YX8_a2ayLrmDiTWjMG0RjaH2fMobm3fmXcBRdSK-7-MYZq6T_-owuLby2sjZNt43WKlkH2Fn2LfRwdno_vIhH1-eXw-NRrChPmliVpcYZzkGkKZZE8IwpqRRRSpdZyQjoTHOmuax4mXCqKdZZ_zauIIWSM8a20MEid-rdawuhKSYmKKhracG1oaCCctHjpHkvpQup8i4ED1Ux9WYifVcQXMyRFz_IiznyYom8N-0v89tyAvrP8gu4F-wtBAYA_iWSJCeCsG-fiYky</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2825810929</pqid></control><display><type>article</type><title>Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality</title><source>IEEE Electronic Library (IEL)</source><creator>Wei, Hongzhi ; Li, Ruoxia</creator><creatorcontrib>Wei, Hongzhi ; Li, Ruoxia</creatorcontrib><description>This article is devoted to solving the exponential synchronization problem of a new type of fuzzy memristive neural network with reaction-diffusion terms. By introducing adaptive laws, two controllers are designed. After combining the inequality technique with the Lyapunov function approach, some easily verified sufficient conditions are established to ensure the exponential synchronization of the reaction-diffusion fuzzy memristive system under the proposed adaptive scheme. In addition, by using the Hardy-Poincarè inequality, the diffusion terms are estimated associated with the information of the reaction-diffusion coefficients and the regional feature, which improves some existing conclusions. Finally, an illustrative example is presented to demonstrate the validity of the theoretical results.</description><identifier>ISSN: 2162-237X</identifier><identifier>ISSN: 2162-2388</identifier><identifier>EISSN: 2162-2388</identifier><identifier>DOI: 10.1109/TNNLS.2023.3281645</identifier><identifier>PMID: 37310829</identifier><identifier>CODEN: ITNNAL</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Biological neural networks ; Exponential synchronization ; fuzzy ; Fuzzy logic ; Hardy–Poincarè inequality ; Integrated circuit modeling ; Learning systems ; memristive ; Memristors ; Neurons ; reaction-diffusion term ; Synchronization</subject><ispartof>IEEE transaction on neural networks and learning systems, 2024-10, Vol.35 (10), p.14825-14832</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c254t-cbbd0709e8660a18573cacc1ccdb7b31ed7d53d5af5b452d20d71620fe6eb5333</citedby><cites>FETCH-LOGICAL-c254t-cbbd0709e8660a18573cacc1ccdb7b31ed7d53d5af5b452d20d71620fe6eb5333</cites><orcidid>0000-0002-4673-9834 ; 0000-0002-4817-9906</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10149181$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10149181$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37310829$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wei, Hongzhi</creatorcontrib><creatorcontrib>Li, Ruoxia</creatorcontrib><title>Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality</title><title>IEEE transaction on neural networks and learning systems</title><addtitle>TNNLS</addtitle><addtitle>IEEE Trans Neural Netw Learn Syst</addtitle><description>This article is devoted to solving the exponential synchronization problem of a new type of fuzzy memristive neural network with reaction-diffusion terms. By introducing adaptive laws, two controllers are designed. After combining the inequality technique with the Lyapunov function approach, some easily verified sufficient conditions are established to ensure the exponential synchronization of the reaction-diffusion fuzzy memristive system under the proposed adaptive scheme. In addition, by using the Hardy-Poincarè inequality, the diffusion terms are estimated associated with the information of the reaction-diffusion coefficients and the regional feature, which improves some existing conclusions. Finally, an illustrative example is presented to demonstrate the validity of the theoretical results.</description><subject>Biological neural networks</subject><subject>Exponential synchronization</subject><subject>fuzzy</subject><subject>Fuzzy logic</subject><subject>Hardy–Poincarè inequality</subject><subject>Integrated circuit modeling</subject><subject>Learning systems</subject><subject>memristive</subject><subject>Memristors</subject><subject>Neurons</subject><subject>reaction-diffusion term</subject><subject>Synchronization</subject><issn>2162-237X</issn><issn>2162-2388</issn><issn>2162-2388</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkMtOwzAQRS0EAgT8AEIoSzYpfsSJww6Vp1QK4iGxixx7IgypXewESL-I_-DHSGlBzGZGM_deaQ5CuwQPCMH54f14PLobUEzZgFFB0oSvoE1KUhpTJsTq35w9bqCdEJ5xXynmaZKvow2WMYIFzTfR2-nH1FmwjZF1dNdZ9eSdNTPZGGejobONd3XkqugWpJrv4hNTVW2YX8_a2ayLrmDiTWjMG0RjaH2fMobm3fmXcBRdSK-7-MYZq6T_-owuLby2sjZNt43WKlkH2Fn2LfRwdno_vIhH1-eXw-NRrChPmliVpcYZzkGkKZZE8IwpqRRRSpdZyQjoTHOmuax4mXCqKdZZ_zauIIWSM8a20MEid-rdawuhKSYmKKhracG1oaCCctHjpHkvpQup8i4ED1Ux9WYifVcQXMyRFz_IiznyYom8N-0v89tyAvrP8gu4F-wtBAYA_iWSJCeCsG-fiYky</recordid><startdate>202410</startdate><enddate>202410</enddate><creator>Wei, Hongzhi</creator><creator>Li, Ruoxia</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4673-9834</orcidid><orcidid>https://orcid.org/0000-0002-4817-9906</orcidid></search><sort><creationdate>202410</creationdate><title>Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality</title><author>Wei, Hongzhi ; Li, Ruoxia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c254t-cbbd0709e8660a18573cacc1ccdb7b31ed7d53d5af5b452d20d71620fe6eb5333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Biological neural networks</topic><topic>Exponential synchronization</topic><topic>fuzzy</topic><topic>Fuzzy logic</topic><topic>Hardy–Poincarè inequality</topic><topic>Integrated circuit modeling</topic><topic>Learning systems</topic><topic>memristive</topic><topic>Memristors</topic><topic>Neurons</topic><topic>reaction-diffusion term</topic><topic>Synchronization</topic><toplevel>online_resources</toplevel><creatorcontrib>Wei, Hongzhi</creatorcontrib><creatorcontrib>Li, Ruoxia</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transaction on neural networks and learning systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wei, Hongzhi</au><au>Li, Ruoxia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality</atitle><jtitle>IEEE transaction on neural networks and learning systems</jtitle><stitle>TNNLS</stitle><addtitle>IEEE Trans Neural Netw Learn Syst</addtitle><date>2024-10</date><risdate>2024</risdate><volume>35</volume><issue>10</issue><spage>14825</spage><epage>14832</epage><pages>14825-14832</pages><issn>2162-237X</issn><issn>2162-2388</issn><eissn>2162-2388</eissn><coden>ITNNAL</coden><abstract>This article is devoted to solving the exponential synchronization problem of a new type of fuzzy memristive neural network with reaction-diffusion terms. By introducing adaptive laws, two controllers are designed. After combining the inequality technique with the Lyapunov function approach, some easily verified sufficient conditions are established to ensure the exponential synchronization of the reaction-diffusion fuzzy memristive system under the proposed adaptive scheme. In addition, by using the Hardy-Poincarè inequality, the diffusion terms are estimated associated with the information of the reaction-diffusion coefficients and the regional feature, which improves some existing conclusions. Finally, an illustrative example is presented to demonstrate the validity of the theoretical results.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>37310829</pmid><doi>10.1109/TNNLS.2023.3281645</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-4673-9834</orcidid><orcidid>https://orcid.org/0000-0002-4817-9906</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2162-237X |
| ispartof | IEEE transaction on neural networks and learning systems, 2024-10, Vol.35 (10), p.14825-14832 |
| issn | 2162-237X 2162-2388 2162-2388 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2825810929 |
| source | IEEE Electronic Library (IEL) |
| subjects | Biological neural networks Exponential synchronization fuzzy Fuzzy logic Hardy–Poincarè inequality Integrated circuit modeling Learning systems memristive Memristors Neurons reaction-diffusion term Synchronization |
| title | Exponential Synchronization Control of Reaction-Diffusion Fuzzy Memristive Neural Networks: Hardy-Poincarè Inequality |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T04%3A04%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Exponential%20Synchronization%20Control%20of%20Reaction-Diffusion%20Fuzzy%20Memristive%20Neural%20Networks:%20Hardy-Poincar%C3%A8%20Inequality&rft.jtitle=IEEE%20transaction%20on%20neural%20networks%20and%20learning%20systems&rft.au=Wei,%20Hongzhi&rft.date=2024-10&rft.volume=35&rft.issue=10&rft.spage=14825&rft.epage=14832&rft.pages=14825-14832&rft.issn=2162-237X&rft.eissn=2162-2388&rft.coden=ITNNAL&rft_id=info:doi/10.1109/TNNLS.2023.3281645&rft_dat=%3Cproquest_RIE%3E2825810929%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2825810929&rft_id=info:pmid/37310829&rft_ieee_id=10149181&rfr_iscdi=true |