Stability of Cohen-Grossberg neural networks with time-varying delays
Stability of Cohen-Grossberg neural networks with time-varying delays
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DOI：
10.1016/j.neunet.2007.07.005
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发表时间：
2007-10
期刊：
影响因子：
--
通讯作者：
Tingwen Huang;Andrew Chan;Yu Huang;Jinde Cao
中科院分区：
文献类型：
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作者：
Tingwen Huang;Andrew Chan;Yu Huang;Jinde Cao
在本文中，我们研究了时变延迟的 Cohen-Grossberg 神经网络平衡点的存在性和稳定性。在易于验证的条件下，当时延有限时获得指数稳定性，而当时延无限时获得渐近稳定。此外，所获得的稳定性是稳健的。延迟项的唯一条件是连续性。这里获得的结果改进并扩展到文献中的结果。
In this paper, we investigate the existence and stability of the equilibrium point of Cohen–Grossberg neural networks with time-varying delays. Under easily verified conditions, exponential stability is obtained when the delay is finite, while asymptotic stability is obtained when the delay is infinite. Moreover, the stability obtained is robust. The only condition for the delay term is continuity. The results obtained here improve and extend to those in the literature.