A Stochastic Neutral Cellular Neural Networks Model Driven by G-Brownian Motion

Ping HE, Yong REN, De-fei ZHANG

Abstract


In this paper, we propose a new stochastic neutral cellular neural networks model with time delay driven by G -Brownian motion (G-SNCNNs for short). By using fixed point theory and G-expectation analysis methods, the exponential stability and some sufficient conditions on the exponential stability in mean square of the solutions for G-SNCNNs are presented. Finally, a typical case is given to illustrate the effectiveness of the theoretical result.

Keywords


Neural network, Exponential stability, Delay, G-Brownian motion


DOI
10.12783/dteees/icepe2019/28939

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