Some Further Results on Fixed-Time Synchronization of Neural Networks with Stochastic Perturbations

In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations.

带分布时滞的模糊神经网络的广义衰减同步

研究了一类具有分布时滞的模糊神经网络的广义衰减同步控制问题.首先通过构造适当的Lyapunov-Krasovskii泛函和设计一种非线性控制器,得到了所考虑的模糊神经网络实现广义衰减同步的充分条件.最后通过数值模拟验证了所得结论的可行性。