Finite-time projective synchronization of memristor-based neural networks with leakage and time-varying delays

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

Physica A: Statistical Mechanics and its Applications, 2019, vol. 531, issue C

Abstract: This paper is concerned with the finite-time projective synchronization problem of memristor-based neural networks(MNNs) with leakage and time-varying delays. The finite-time modified projective synchronization and function projective synchronization theorems are proposed, and the approach of Lyapunov stability and two different finite-time synchronization methods are adopted in the proof processes. Based on time-delay correlation and irrelevant problem, two different controllers are designed, and several stability conditions are presented to ensure that the drive–response systems achieve the finite-time synchronization with arbitrary continuous bounded functions. Meanwhile, several corollaries about the special cases of finite-time projective synchronization are given along with the theorems. Finally, two numerical simulations are carried out to illustrate the effectiveness and verify our results.

Keywords: Finite-time synchronization; Memristor-based neural networks(MNNs); Leakage delay; Projective synchronization (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:531:y:2019:i:c:s037843711931043x

DOI: 10.1016/j.physa.2019.121788

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