Finite-/Fixed-Time Synchronization of Coupled Memristive Neural Networks With Actuator Nonlinearity and Applications in Secure Communication
Mingxin Wang, Song Zhu, Weiwei Luo, Zhen Zhang
Abstract
This paper investigates the synchronization control of coupled memristive neural networks (CMNNs) and its application in secure communication. First of all, a CMNNs system model that accommodates input saturation and dead-zone is introduced duo to the actuator nonlinearity is a common problem in practical network control. On which basis, a secure communication scheme containing multiple information receivers is proposed, which strengthened the security of communication through the coupling characteristics between states. Next, by using the adaptive control method and the Lyapunov stability theory, an adaptive finite-time synchronization strategy is proposed for the considered CMNNs. Following, an adaptive fixed-time synchronization strategy is proposed to further improve the flexibility of control schemes and reduce the impact of system initial values. Each designed controller not only ensures the synchronization of the CMNNs, but also guarantees the stability of the designed secure communication system. In the end, feasibilities of synchronization strategies and communication scheme are proved through simulation experiments.