A New Switching System Protocol for Synchronization in Probability of RDNNs With Stochastic Sampling
针对随机采样下的反应扩散神经网络，提出一种新型切换系统协议，设计随机切换采样数据控制器，建立概率同步判据，并通过数值例子验证有效性。
The synchronization in probability of reaction-diffusion neural networks (RDNNs) with stochastic sampling is studied in this article. By introducing a stochastic switching parameter, a new switching system protocol is proposed for stochastic sampling control systems. The switching system protocol effectively improves the existing methods. By the protocol, the stochastic switching sampled-data controller is designed, and the considered system is transformed into a switching system. Different from the existing sampled-data controllers with determined control gains, the stochastic switching sampled-data controller is with switching gains, which is more elastic. Then, by constructing a new stochastic switching Lyapunov–Krasovskii functional (LKF), using the law of large numbers and the Lagrange mean value theorem, new synchronization in probability criteria are established for RDNNs. In the mean time, the wanted stochastic switching sampled-data controller gains are obtained. Moreover, the synchronization in probability issue is also studied for NNs with stochastic sampling. Finally, the effectiveness of the proposed results are verified by two numerical examples.