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Article type: Research Article
Authors: Fei, Kaifanga; b | Jiang, Minghuia; b; * | Zhang, Yadana; b
Affiliations: [a] Institute of Nonlinear Complex Systems, China Three Gorges University, YiChang, Hubei, China | [b] Three Gorges Mathematical Research Center, China Three Gorges University, China
Correspondence: [*] Corresponding author. Minghui Jiang, Institute of Nonlinear Complex Systems, China Three Gorges University, YiChang, Hubei 443000, China. E-mail: [email protected].
Abstract: In this paper, the matters of dissipativity and finite time synchronization for memristor-based neural networks (MNNs) with mixed time-varying discontinuities are investigated. Firstly, under the framework of extending Filippov differential inclusion theory, several effective new criteria are derived. Then, the global dissipativity of Filippov solution to neural networks is proved by using generalized Halanay inequality and matrix measure method. Secondly, some novel sufficient conditions are introduced to guarantee the finite-time synchronization of the drive-response MNNs based on a simple Lyapunov function and two different feedback controllers. Finally, several numerical examples are given to verify the validity of the theoretical results.
Keywords: Memristor, dissipativity, finite time synchronization, mixed time-varying delayed, neural networks
DOI: 10.3233/JIFS-191397
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1695-1712, 2021
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