Global stability of Hopfield neural networks under dynamical thresholds with distributed delays
We study the dynamical behavior of a class of Hopfield neural networks with distributed delays under dynamical thresholds. Some new criteria ensuring the existence, uniqueness, and global asymptotic stability of equilibrium point are derived. In the results, we do not require the activation function...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2006-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/DDNS/2006/27941 |
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| Summary: | We study the dynamical behavior of a class of Hopfield neural
networks with distributed delays under dynamical thresholds. Some
new criteria ensuring the existence, uniqueness, and global
asymptotic stability of equilibrium point are derived. In the
results, we do not require the activation functions to satisfy the
Lipschitz condition, and also not to be bounded, differentiable,
or monotone nondecreasing. Moreover, the symmetry of the
connection matrix is not also necessary. Thus, our results improve
some previous works in the literature. These conditions have great
importance in designs and applications of the global asymptotic
stability for Hopfield neural networks involving distributed
delays under dynamical thresholds. |
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| ISSN: | 1026-0226 1607-887X |