Finite-time modified projective synchronization of memristor-based neural network with multi-links and leakage delay

Xiaoli Qin, Cong Wang, Lixiang Li, Haipeng Peng, Yixian Yang and Lu Ye

Chaos, Solitons & Fractals, 2018, vol. 116, issue C, 302-315

Abstract: This paper investigates the finite-time modified projective synchronization problem of memristor-based neural networks with multi-links (MNNLs). And leakage and discrete time-varying delays (mixed delays) are considered in the MNNLs model. By designing a delay-dependent controller and an adaptive controller, the drive-response systems can reach finite-time modified projective synchronization with arbitrary constants. Based on two kinds of finite-time stability theories and some differential inequalities, several finite-time modified projective synchronization criteria are obtained with the Lyapunov stability method. Besides, several corollaries about the special cases of finite-time modified projective synchronization are given along with the proposed theorems. At last, three numerical simulations are given to illustrate the effectiveness and verify the correctness of our results.

Keywords: Memristor-based neural networks with multi-links (MNNLs); Leakage delay; Finite-time synchronization; Modified projective synchronization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:116:y:2018:i:c:p:302-315

DOI: 10.1016/j.chaos.2018.09.040

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