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考虑了一个具有多重时变时滞的随机神经网络的全局渐近稳定性问题.通过构造Lyapunov-Krasovskii函数并运用广义Ito公式,得到了一个充分条件,条件保证了神经网络在随机扰动下的全局均方渐近稳定性.最后通过一个数值实例验证了结果的有效性.
Considering the global asymptotic stability of a stochastic neural network with multiple time-varying delays, a sufficient condition is obtained by constructing the Lyapunov-Krasovskii function and using the generalized Ito formula. The conditions ensure that the global stability of the neural network under stochastic disturbances Asymptotically stability of the mean square. Finally, a numerical example is given to verify the validity of the result.