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New convergence on inertial neural networks with time-varying delays and continuously distributed delays

Qian Cao Xin Long

*Corresponding author: Xin Long longxinxinxin@126.com

Math2020,6,5955doi:10.3934/math.2020381

In this paper, a class of inertial neural networks with bounded time-varying delays and unbounded continuously distributed delays are explored by applying non-reduced order method. Based upon differential inequality techniques and Lyapunov function method, a new sufficient condition is presented to ensure all solutions of the addressed model and their derivatives converge to zero vector, which refines some previously known researches. Moreover, a numerical example is provided to illustrate these analytical conclusions.

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