Dynamic Pinning Synchronization of Fuzzy-Dependent-Switched Coupled Memristive Neural Networks With Mismatched Dimensions on Time Scales
Xiangxiang Wang, Yongbin Yu, Jingye Cai, Shouming Zhong, Nijing Yang, Kaibo Shi, Pinaki Mazumder, Nyima Tashi
Abstract
This article addresses the problem of dynamic pinning synchronization of fuzzy-dependent-switched (Fds) coupled memristive neural networks (CMNNs) with mismatched dimensions on time scales. To begin with, the probabilistic coupling delays, time scales, mismatched dimensions, and function projective synchronization rules are considered to design the novel CMNNs to improve the reliability and generalization ability of the model. Then Fds rules and dynamic pinning control (DPC) method are adopted to design the CMNNs, which can effectively promote the information exchange between the switching signals and the fuzzy processes and can improve the utilization of the communication bandwidth between the nodes of CMNNs. Meanwhile, the method of constructing auxiliary state variables is adopted here to deal with the presented model, so that the coupled and isolated systems with different dimensions can realize information exchange and data sharing. This method also provides a solution for researchers by using low-dimensional systems to estimate or synchronize high-dimensional systems. Moreover, by means of Lyapunov–Krasovskii functional, auxiliary orthogonal matrix, and some inequality processing techniques, the conditions of modified function projective synchronization for Fds CMNNs are derived via the DPC on time scales. Finally, two numerical examples are provided to illustrate the effectiveness of the main results.