Discrete-time Cohen-Grossberg neural networks(CGNNs) are studied in this paper. Several sufficient conditions are obtained to ensure the global exponential stability of the discrete-time systems of CGNNs with delays based on Lyapunov methods. The obtained results have not assume the symmetry of the connection matrix, and monotonicity, boundness of the activation functions. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Sun, C., Ju, L., Liang, H., & Wang, S. (2007). Exponential stability of discrete-time Cohen-Grossberg neural networks with delays. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 920–925). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_107
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