In this paper, we study the global asymptotic stability properties of cellular neural networks with variable coefficients and time varying delays. We present sufficient conditions for the global asymptotic stability of the neural networks . The proposed conditions, which are applicable to all continuous nonmonotonic neuron activation functions and do not require the interconnection matrices to be symmetric, establish the relationships between network parameters of the neural systems and the delay parameters. Some examples show that our results are new and improve the previous results derived in the literature. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kao, Y., Gao, C., & Zhang, L. (2007). Global asymptotic stability of cellular neutral networks with variable coefficients and time-varying delays. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 910–919). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_106
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