We derive some sufficient conditions for the existence of a square-mean almost automorphic solution for a stochastic cellular neural network on time scales by using Krasnoselskii’s fixed point theorem. The Banach contraction principle is also used to show the uniqueness of a solution with some additional restrictions. Exponential stability of the obtained solution is also discussed by taking a suitable Lyapunov functional on time scale. At the end, we give a numerical example to illustrate the effectiveness of the obtained theoretical results. Our results are valid for general time scale, and the cases or are particular cases.
"Square-mean almost automorphic solution of a stochastic cellular neural network on time scales." J. Integral Equations Applications 32 (2) 151 - 170, Summer 2020. https://doi.org/10.1216/jie.2020.32.151