时标上一类递归神经网络反周期解的存在唯一性与全局指数稳定性

Existence uniqueness and globally exponential stability of anti-periodic solution for a class of recurrent neural networks on time scales

使用重合度方法和M-矩阵理论,得到时标上一类具有脉冲与分布时滞的递归神经网络反周期解的存在唯一性与全局指数稳定的充分条件.最后,通过1个例子说明结论的有效性.

This work use the continuation theorem of coincidence degree theory,M-matrix theory to study the existence,uniqueness and exponential stability of anti-periodic solutions of a class of impulsive recurrent neural networks with distributed delayson time scales.Finally,an example is given to illustrate the effectiveness of main results.