变系数高阶模糊神经网络的指数收敛性

Exponential convergence of high-order fuzzy cellular neural networks with time-varying coefficients

研究了高阶变系数模糊神经网络的动力学行为,得到了保证高阶模糊神经网络的解指数收敛的充分条件.与文献中已有结论相比,本文得到的充分条件中既不要求激活函数满足利普希茨连续条件,也不要求时滞延迟满足可微条件,因而具有更大的适用范围.

The dynamic behavior of high-order fuzzy cellular neural networks （HFCNNs） with time- varying coefficients and delays are considered. Some sufficient conditions are derived for the exponential convergence of such HFCNNs. Compared with the previous results, the new criteria in this paper do not require the Lipschitz continuous condition and the differentiability of variable delays, and so have less conservation.