Adaptive Synchronization of Stochastic Memristor-Based Neural Networks with Mixed Delays

Article

DOI: 10.1007/s11063-017-9623-5

Cite this article as:
Song, Y. & Sun, W. Neural Process Lett (2017). doi:10.1007/s11063-017-9623-5

Abstract

In this paper, adaptive synchronization of stochastic memristor-based neural networks with mixed delays is investigated. By using the differential inclusions theory, adaptive control technique and stochastic Lyapunov method, two adaptive updated laws are designed and two synchronization criteria are derived for stochastic memristor-based neural networks with mixed delays. The derived criteria complement and improve the previously known results since stochastic perturbations and mixed delays are considered. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical results.

Keywords

Adaptive synchronization Stochastic memristor-based neural networks Mixed delays Lyapunov functional 

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.School of Information and MathematicsYangtze UniversityJingzhouChina

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