一类具比例时滞递归神经网络的全局指数稳定性

Global exponential stability of a class of recurrent neural networks with proportional delays

应用同胚映射理论和构造合适的Lyapunov泛函,以及结合Young不等式,研究一类具比例时滞递归神经网络的全局指数稳定性,得到了该系统平衡点存在唯一且全局指数稳定的充分条件.通过数值算例及其仿真结果验证了所得结论的正确性.

By applying homeomorphic mapping theorem and constructing appropriate Lyapunov functional, and combining Young inequality, the global exponential stability of a class of recurrent neural networks with proportional delays is studied. Several sufficient conditions are derived for the existence and uniqueness of the considered system and global exponential stability of the equilibrium point, A numerical example and its simulation results are given to illustrate the correctness of the obtained conclusion.