Global exponential stability of delayed inertial competitive neural networks
Min Shi, Juan Guo, Xianwen Fang, Chuangxia Huang · Advances in Difference Equations · 2020
Abstract In this paper, the exponential stability for a class of delayed competitive neural networks is studied. By applying the inequality technique and non-reduced-order approach, some novel and useful criteria of global exponential stability for the addressed network model are established. Moreover, a numerical example is presented to show the feasibility and effectiveness of the theoretical results.