Quasi-projective and complete synchronization of fractional-order complex-valued neural networks with time delays
This paper studies quasi-projective synchronization (QPS) and complete synchronization (CS) for a class of fractional-order complex-valued neural networks with time delays by designing suitable controllers. To realize QPS and CS, linear feedback controller and adaptive controller are designed, and a...
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| Veröffentlicht in: | Neural networks 2019-10, Vol.118, p.102-109 |
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| container_title | Neural networks |
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| creator | Li, Hong-Li Hu, Cheng Cao, Jinde Jiang, Haijun Alsaedi, Ahmed |
| description | This paper studies quasi-projective synchronization (QPS) and complete synchronization (CS) for a class of fractional-order complex-valued neural networks with time delays by designing suitable controllers. To realize QPS and CS, linear feedback controller and adaptive controller are designed, and a novel fractional-order differential inequality is built by means of Laplace transform and properties of Mittag-Leffler function. By utilizing Lyapunov method, our proposed inequality, fractional-order Razumikhin theorem and some complex analysis techniques, some effective criteria are derived to ensure QPS and CS of the considered networks. Furthermore, the error bound of QPS is obtained. Finally, some numerical results are given to demonstrate the effectiveness of the presented theoretical results. |
| doi_str_mv | 10.1016/j.neunet.2019.06.008 |
| format | Article |
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To realize QPS and CS, linear feedback controller and adaptive controller are designed, and a novel fractional-order differential inequality is built by means of Laplace transform and properties of Mittag-Leffler function. By utilizing Lyapunov method, our proposed inequality, fractional-order Razumikhin theorem and some complex analysis techniques, some effective criteria are derived to ensure QPS and CS of the considered networks. Furthermore, the error bound of QPS is obtained. 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Finally, some numerical results are given to demonstrate the effectiveness of the presented theoretical results.</description><subject>Algorithms</subject><subject>Complete synchronization</subject><subject>Complex-valued neural networks</subject><subject>Feedback</subject><subject>Fractional-order</subject><subject>Neural Networks, Computer</subject><subject>Quasi-projective synchronization</subject><subject>Time delays</subject><subject>Time Factors</subject><issn>0893-6080</issn><issn>1879-2782</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1v1DAQhi0EokvhHyDkI5eEsZ3YzgUJVS0gVUJI5Ww5zkT1ksRb29my_fX1aheOnGYOzzsfDyHvGdQMmPy0rRdcF8w1B9bVIGsA_YJsmFZdxZXmL8kGdCcqCRouyJuUtgAgdSNekwvBeNso2W7Iw8_VJl_tYtiiy36P1C4DdWHeTZiRpsPi7mNY_JPNPiw0jHSM1h17O1UhDhjP8J9qb6cVB1quinYqJT-G-DvRR5_vafYz0gEne0hvyavRTgnfnesl-XVzfXf1rbr98fX71ZfbygnJc8W04NyBalUnVdOW053iDJyzIzR930rV677pRylEx3TnHMPB8gZ65UQHKMQl-XiaW357WDFlM_vkcJrsgmFNhvMWpOBNxwranFAXQ0oRR7OLfrbxYBiYo2yzNSfZ5ijbgDRFdol9OG9Y-xmHf6G_dgvw-QRg-XPvMZrkPC4OBx-LbTME__8Nz-mFlHQ</recordid><startdate>201910</startdate><enddate>201910</enddate><creator>Li, Hong-Li</creator><creator>Hu, Cheng</creator><creator>Cao, Jinde</creator><creator>Jiang, Haijun</creator><creator>Alsaedi, Ahmed</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3133-7119</orcidid></search><sort><creationdate>201910</creationdate><title>Quasi-projective and complete synchronization of fractional-order complex-valued neural networks with time delays</title><author>Li, Hong-Li ; Hu, Cheng ; Cao, Jinde ; Jiang, Haijun ; Alsaedi, Ahmed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-18322c075796745006c7210ccaf04bb567b8b4bf6339189cc1eda240b7c390e33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Complete synchronization</topic><topic>Complex-valued neural networks</topic><topic>Feedback</topic><topic>Fractional-order</topic><topic>Neural Networks, Computer</topic><topic>Quasi-projective synchronization</topic><topic>Time delays</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Hong-Li</creatorcontrib><creatorcontrib>Hu, Cheng</creatorcontrib><creatorcontrib>Cao, Jinde</creatorcontrib><creatorcontrib>Jiang, Haijun</creatorcontrib><creatorcontrib>Alsaedi, Ahmed</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Neural networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Hong-Li</au><au>Hu, Cheng</au><au>Cao, Jinde</au><au>Jiang, Haijun</au><au>Alsaedi, Ahmed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quasi-projective and complete synchronization of fractional-order complex-valued neural networks with time delays</atitle><jtitle>Neural networks</jtitle><addtitle>Neural Netw</addtitle><date>2019-10</date><risdate>2019</risdate><volume>118</volume><spage>102</spage><epage>109</epage><pages>102-109</pages><issn>0893-6080</issn><eissn>1879-2782</eissn><abstract>This paper studies quasi-projective synchronization (QPS) and complete synchronization (CS) for a class of fractional-order complex-valued neural networks with time delays by designing suitable controllers. 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| ispartof | Neural networks, 2019-10, Vol.118, p.102-109 |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Algorithms Complete synchronization Complex-valued neural networks Feedback Fractional-order Neural Networks, Computer Quasi-projective synchronization Time delays Time Factors |
| title | Quasi-projective and complete synchronization of fractional-order complex-valued neural networks with time delays |
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