{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:20:29Z","timestamp":1777702829059,"version":"3.51.4"},"reference-count":0,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2015,1]]},"abstract":"<jats:p>A new adaptive learning control strategy is used to solve the synchronization problem for delayed reaction-diffusion fuzzy cellular neural networks with unknown periodically time-varying parameters. By constructing suitable Lyapunov-Krasovskii-like composite energy functional and employing some analysis techniques, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to achieve the adaptive synchronization of reaction-diffusion fuzzy cellular neural networks with unknown periodically time-varying parameters. Finally, a numerical example is presented to show the effectiveness of the proposed synchronization approach.<\/jats:p>","DOI":"10.3233\/ifs-141283","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T19:20:25Z","timestamp":1575314425000},"page":"141-150","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Adaptive synchronization of delayed reaction-diffusion FCNNs via learning control approach"],"prefix":"10.1177","volume":"28","author":[{"given":"Weiyuan","family":"Zhang","sequence":"first","affiliation":[{"name":"The State Key Laboratory for Manufacturing System Engineering, and System Engineering Institute, Xi'an Jiaotong University, Xi'an Shaanxi, China"},{"name":"Institute of Nonlinear Science, Xianyang Normal University, Xianyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keyi","family":"Xing","sequence":"additional","affiliation":[{"name":"The State Key Laboratory for Manufacturing System Engineering, and System Engineering Institute, Xi'an Jiaotong University, Xi'an Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junmin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Science, Xidian University, Xi'an Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minglai","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Science, Xidian University, Xi'an Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2015,1]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-141283","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-141283","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:37:00Z","timestamp":1777455420000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-141283"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,1]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,1]]}},"alternative-id":["10.3233\/IFS-141283"],"URL":"https:\/\/doi.org\/10.3233\/ifs-141283","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,1]]}}}