Synchronization of stochastic delayed neural networks with markovian switching and its application.
In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.
Tang
Yang
Y
Department of Automation, Donghua University, No. 300 Wenhui Road, Shanghai, 201620, China. Tangtany@gmail.com
Fang
Jian-An
JA
Miao
Qing-Ying
QY
D000223:Adaptation, Psychological / Q000502:physiology*; D001676:Biofeedback, Psychology / Q000502:physiology*; D006801:Humans; D008390:Markov Chains; D016571:Neural Networks, Computer; D011930:Reaction Time / Q000502:physiology*; D013997:Time Factors