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This paper is concerned with Hopfield neural networks with unbounded time-varying delay driven by G-Brownian motion. The existence and uniqueness of solutions, as well as the continuity of solutions in the sense of G-mean square, are investigated for such neural networks. Moreover, sufficient conditions dependent on delay are derived to guarantee G-mean square asymptotic stability and G-mean square exponential stability of neural networks. At last, two examples are provided to illustrate the application of the obtained results.

Stability analysis of Hopfield neural networks with unbounded delay driven by G-Brownian motion