Abstract
The robust stability of a class of Hopfield neural networks with multiple delays is analyzed. Sufficient conditions for the global robust stability of the equilibrium point are established through constructing a suitable Lyapunov-Krasovskii functional. The present results take the form of linear matrix inequalities, and are computationally efficient. In addition, the results are independent of delays and established without assuming differentiability and monotonicity of the activation function.
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Zhang, H., Ji, C., Liu, D. (2005). Robust Stability Analysis of a Class of Hopfield Neural Networks with Multiple 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_32
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DOI: https://doi.org/10.1007/11427391_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
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