Shenping Xiao, Lin-Xing Xu, Gang Chen, Lingshuang Kong
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Globally asymptotic stability for neural networks with time-varying delay via delay-decomposition approach
In this article, the problem of the stability for delay-dependent neural networks is concerned. A new Lyapunov-Krasovskii functional is introduced, so as to obtain some more superior delay-dependent stability criterion. Moreover, by employing the delay decomposition technique, some novel absolute stability conditions are established, which refine and improve some existing ones. Finally, the feasibility and superiority of the proposed method is demonstrated by a numerical example.