Abstract
This paper presents several exponential stability criteria for delayed neural networks with time-varying delays and a general class of activation functions, which are derived by employing Lyapyunov-Krasovskii functional approach and linear matrix inequality technique. The proposed results are shown theoretically and numerically to be less restrictive and more easily verified than those reported recently in the open literature. In addition, an approach to estimate the degree of exponential convergence is also formulated.
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Wu, D., Xiong, Q., Li, C., Zhang, Z., Tang, H. (2005). Improved Results for Exponential Stability of Neural Networks with Time-Varying Delays. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_19
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DOI: https://doi.org/10.1007/11427391_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
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