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Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling
Joint Authors
Liu, Haidong
Xia, Yonghui
Ye, Lixia
Yan, Jin-liang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-23
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper concerns the synchronization problem for a class of stochastic memristive neural networks with inertial term, linear coupling, and time-varying delay.
Based on the interval parametric uncertainty theory, the stochastic inertial memristor-based neural networks (IMNNs for short) with linear coupling are transformed to a stochastic interval parametric uncertain system.
Furthermore, by applying the Lyapunov stability theorem, the stochastic analysis approach, and the Halanay inequality, some sufficient conditions are obtained to realize synchronization in mean square.
The established criteria show that stochastic perturbation is designed to ensure that the coupled IMNNs can be synchronized better by changing the state coefficients of stochastic perturbation.
Finally, an illustrative example is presented to demonstrate the efficiency of the theoretical results.
American Psychological Association (APA)
Ye, Lixia& Xia, Yonghui& Yan, Jin-liang& Liu, Haidong. 2020. Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling. Complexity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1142460
Modern Language Association (MLA)
Ye, Lixia…[et al.]. Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling. Complexity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1142460
American Medical Association (AMA)
Ye, Lixia& Xia, Yonghui& Yan, Jin-liang& Liu, Haidong. Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling. Complexity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1142460
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142460