 New criteria for globally exponential stability of delayed Cohen–Grossberg neural networkShengshuang Chen, Weirui Zhao and Yong Xu Mathematics and Computers in Simulation (MATCOM), 2009, vol. 79, issue 5, 1527-1543 Abstract: This paper is concerned with analysis problem for the global exponential stability of the Cohen–Grossberg neural networks with discrete delays and with distributed delays. We first prove the existence and uniqueness of the equilibrium point under mild conditions, assuming neither differentiability nor strict monotonicity for the activation function. Then, we employ Lyapunov functions to establish some sufficient conditions ensuring global exponential stability of equilibria for the Cohen–Grossberg neural networks with discrete delays and with distributed delays. Our results are not only presented in terms of system parameters and can be easily verified and also less restrictive than previously known criteria. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed neural networks. Keywords: Global exponential stability (GES); Lyapunov functional; Neural networks; Delays (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:79:y:2009:i:5:p:1527-1543 DOI: 10.1016/j.matcom.2008.07.002 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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