A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network

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dc.contributor.author Wang, Ran
dc.contributor.author Li, Chunbiao
dc.contributor.author Çiçek, Serdar
dc.contributor.author Rajagopal, Karthikeyan
dc.contributor.author Zhang, Xin
dc.date.accessioned 2021-04-20T14:53:59Z
dc.date.available 2021-04-20T14:53:59Z
dc.date.issued 2021
dc.identifier.citation R. Wang, C. Li, S. ÇİÇEK, K. Rajagopal, and X. Zhang, “A Memristive Hyperjerk Chaotic System Amplitude Control FPGA Design and Prediction with Artificial Neural Network,” Complexity, vol. 2021, pp. 0–0, Feb. 2021. tr_TR
dc.identifier.uri https://www.hindawi.com/journals/complexity/2021/6636813/
dc.identifier.uri http://hdl.handle.net/20.500.11787/1305
dc.description.abstract An amplitude controllable hyperjerk system is constructed for chaos producing by introducing a nonlinear factor of memristor. In this case, the amplitude control is realized from a single coefficient in the memristor. The hyperjerk system has a line of equilibria and also shows extreme multistability indicated by the initial value-associated bifurcation diagram. FPGA-based circuit realization is also given for physical verification. Finally, the proposed memristive hyperjerk system is successfully predicted with artificial neural networks for AI based engineering applications. tr_TR
dc.language.iso eng tr_TR
dc.publisher Hindawi tr_TR
dc.relation.isversionof 10.1155/2021/6636813 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Memristive tr_TR
dc.subject Hyperjerk Chaotic System tr_TR
dc.subject FPGA tr_TR
dc.subject Artificial Neural Network tr_TR
dc.title A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network tr_TR
dc.type article tr_TR
dc.relation.journal Complexity tr_TR
dc.contributor.department Nevşehir Hacıbektaş Veli Üniversitesi, Hacıbektaş Meslek Yüksekokulu, Elektronik ve Otomasyon Bölümü tr_TR
dc.contributor.authorID 33672 tr_TR
dc.identifier.volume 2021 tr_TR
dc.identifier.startpage 6636813 tr_TR


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