Bipartite Synchronization of Fractional-Order Memristor-Based Coupled Delayed Neural Networks with Pinning Control

P. Babu Dhivakaran, A. Vinodkumar (), S. Vijay, S. Lakshmanan, J. Alzabut (), R. A. El-Nabulsi and W. Anukool
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P. Babu Dhivakaran: Department of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India
A. Vinodkumar: Department of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India
S. Vijay: Department of Mathematics, Government Arts College, Udhagamandalam 643002, India
S. Lakshmanan: Division of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai 600127, India
J. Alzabut: Department of Mathematics and General Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
R. A. El-Nabulsi: Research Center for Quantum Technology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
W. Anukool: Research Center for Quantum Technology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

Mathematics, 2022, vol. 10, issue 19, 1-13

Abstract: This paper investigates the bipartite synchronization of memristor-based fractional-order coupled delayed neural networks with structurally balanced and unbalanced concepts. The main result is established for the proposed model using pinning control, fractional-order Jensen’s inequality, and the linear matrix inequality. Further, new sufficient conditions are derived using the Lyapunov–Krasovskii functional with delay-dependent criteria. Finally, numerical simulations are provided including two numerical examples to show the effectiveness of the theoretical results.

Keywords: bipartite synchronization; Filippov sense; memristor; structurally balanced; Caputo derivative; pinning control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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