Song, Qiankun; Zhang, Jiye Global exponential stability of impulsive Cohen-Grossberg neural network with time-varying delays. (English) Zbl 1142.34046 Nonlinear Anal., Real World Appl. 9, No. 2, 500-510 (2008). Summary: An impulsive Cohen-Grossberg neural network model with time-varying delays is considered. Applying the ideas of vector Lyapunov function, \(M\)-matrix theory and inequality technique, several new sufficient conditions are obtained to ensure global exponential stability of the equilibrium point for impulsive Cohen-Grossberg neural network with time-varying delays. These results generalize a few previous known results and remove some restrictions on the neural network. An example is given to show the effectiveness of the obtained results. Cited in 58 Documents MSC: 34K20 Stability theory of functional-differential equations 92B20 Neural networks for/in biological studies, artificial life and related topics 34K45 Functional-differential equations with impulses 34K60 Qualitative investigation and simulation of models involving functional-differential equations Keywords:global exponential stability; Cohen-Grossberg neural network; time-varying delays; impulsive; \(M\)-matrix PDFBibTeX XMLCite \textit{Q. Song} and \textit{J. Zhang}, Nonlinear Anal., Real World Appl. 9, No. 2, 500--510 (2008; Zbl 1142.34046) Full Text: DOI References: [1] Akca, H.; Alassar, R.; Covachev, V.; Covacheva, Z.; Al-Zahrani, E., Continuous-time additive Hopfield-type neural networks with impulses, J. Math. Anal. Appl., 290, 2, 436-451 (2004) · Zbl 1057.68083 [2] Cao, J. D.; Liang, J. L., Boundedness and stability for Cohen-Grossberg neural network with time-varying delays, J. Math. Anal. Appl., 296, 665-685 (2004) · Zbl 1044.92001 [3] Chen, T. 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