带有两个时滞的不确定神经网络的渐近稳定性分析

Asymptotically stability analysis of uncertain neural networks with two time delays

研究一类具有两个时滞和不确定性神经网络的全局渐近稳定性问题,通过构造新的Lyapunov函数,运用线性矩阵不等式理论将T-S模糊模型扩展到带有两个时滞的含有不确定项模糊神经网络,并给出系统稳定的充分条件。仿真实例验证了结论的有效性。

The global asymptotic stability of fuzzy Hopfield neural networks with uncertain parameters and time - varying delays were investigated. By framing Lyapunov function and using linear matrix inequality （LMI） theory, the T- S fuzzy model representation is extended to the stability analysis for uncertain fuzzy neural networks with two time delays. The sufficient conditions for system stability are given. Some numerical examples are given to illustrate theoretically the effectiveness of the method proposed.