Square-mean almost automorphic solution of a stochastic cellular neural network on time scales (Q2214105)

In this paper, through Krasnoselskii's fixed point theorem, the authors establish some sufficient conditions for the existence of a square-mean almost automorphic solution for a stochastic cellular neural network on time scales. By adopting the contraction mapping principle, the authors prove the uniqueness of a solution under some additional restrictions. Also, some sufficient conditions to guarantee the exponential stability of the obtained solution are obtained and a numerical example is provided to illustrate these results.