Synchronization Control of Coupled Memristor-Based Neural Networks with Mixed Delays and Stochastic Perturbations

  • Chuan Chen
  • Lixiang Li
  • Haipeng Peng
  • Yixian Yang
  • Tao Li
Article

Abstract

This paper investigates the synchronization control problem of coupled memristor-based neural networks (CMNNs) with mixed delays and stochastic perturbations. By utilizing simple feedback controllers, some novel sufficient conditions are derived to ensure the exponential synchronization of CMNNs with mixed delays and stochastic perturbations in mean square. In addition, by means of adaptive feedback controllers, the asymptotic synchronization of CMNNs with mixed delays and stochastic perturbations in mean square can also be achieved via stochastic LaSalle invariance principle. Numerical simulations are presented to illustrate the effectiveness of the theoretical results.

Keywords

Synchronization Stochastic perturbations Mixed delays Coupled memristor-based neural networks Feedback controllers 

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Information Security Center, State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.State Key Laboratory of Public Big DataGuizhouChina
  3. 3.College of Computer ScienceSichuan UniversitySichuanChina

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