Convergence on non-autonomous inertial neural networks with unbounded distributed delays
Yanli Xu · Journal of Experimental & Theoretical Artificial Intelligence · 2019
In this paper, without using reduced-order method, a class of non-autonomous inertial neural networks with time-varying connection weights and unbounded continuously distributed delays are considered. Based upon Lyapunov function method and differential inequality technique, some sufficient conditions are established to reveal that all solutions of the addressed model and their derivatives converge to zero vector, which extend and complement earlier ones in the literature. Moreover, a numerical example is provided to illustrate the correctness of the theoretical results.