New delay-dependent exponential stability criteria of BAM neural networks with time delays
New delay-dependent exponential stability criteria of BAM neural networks with time delays
复制标题
具有时滞的 BAM 神经网络新的时滞相关指数稳定性准则
DOI：
10.1016/j.matcom.2008.08.014
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
研究了具有时滞的双向联想记忆网络的全局指数稳定性。基于Lyapunov泛函方法和线性矩阵不等式技术，给出了时滞双向联想记忆神经网络全局指数稳定的几个新的充分条件。就我们所知，这种“线性化”方法用于时滞神经网络模型的指数稳定性分析的报道很少。该方法称为参数化一阶模型变换，用于神经网络的变换。所得条件比文献报道的条件要保守和严格得多。文中还给出了两个数值模拟来说明我们结果的有效性。
In this paper, the global exponential stability is investigated for the bi-directional associative memory networks with time delays. Several new sufficient conditions are presented to ensure global exponential stability of delayed bi-directional associative memory neural networks based on the Lyapunov functional method as well as linear matrix inequality technique. To the best of our knowledge, few reports about such “linearization” approach to exponential stability analysis for delayed neural network models have been presented in literature. The method, called parameterized first-order model transformation, is used to transform neural networks. The obtained conditions show to be less conservative and restrictive than that reported in the literature. Two numerical simulations are also given to illustrate the efficiency of our result.
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DOI：
10.1109/tcsi.2002.800842
发表时间：
2002-08
影响因子：
5.1
作者：
X. Liao;Guanrong Chen;E. Sánchez
通讯作者：
X. Liao;Guanrong Chen;E. Sánchez
影响因子：
7.8
作者：
Xia Huang;Jinde Cao;De-shuang Huang
通讯作者：
Xia Huang;Jinde Cao;De-shuang Huang
DOI：
10.1109/icosp.2000.893435
发表时间：
2000-08
期刊：
WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000
影响因子：
--
作者：
Jinde Cao
通讯作者：
Jinde Cao
影响因子：
7.8
作者：
Q. Song;Jinde Cao
通讯作者：
Q. Song;Jinde Cao
DOI：
10.1016/0167-2789(94)90043-4
发表时间：
1994-09
期刊：
Physica D: Nonlinear Phenomena
影响因子：
--
作者：
K. Gopalsamy;Xue-zhong He
通讯作者：
K. Gopalsamy;Xue-zhong He