Stability analysis of uncertain bi-directional associative memory neural networks with variable delays
不确定双向联想记忆神经网络的稳定性分析

The robust stability of equilibrium point is studied for bi-directional associative memory neural networks with parameter uncertainties and time-varying delays.When the activation function satisfies the condition of Lipschitz continuity,two sufficient conditions are established for the globally robust stability of the equilibrium point by suitably choosing Lyapunov-Krasovskii functional.The obtained results,which take account of the effects of neural inhibitory and excitatory on neural networks,are independent of the sizes of the time-varying delays and are easy to be checked by the interior-point algorithms in MATLAB toolbox.They are compared with prior results in a remark,and are demonstrated by two numerical examples for their effectiveness.