1. 东北大学信息科学与工程学院,辽宁,沈阳,110004
2. 墨西哥国立理工大学自动控制系,墨西哥,07360
3. 东北大学系统科学研究所,辽宁,沈阳,110004
4. 东北大学信息科学与工程学院辽宁沈阳,110004
5. 墨西哥国立理工大学自动控制系墨西哥,07360
6. 东北大学系统科学研究所辽宁沈阳,110004
纸质出版:2008
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王占山, 张化光, 余 文, 等. 基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性[J]. 电子学报, 2008,36(11):2220-2223.
WANG Zhan-shan, ZHANG Hua-guang, YU Wen, et al. An LMI Approach to Robust Stability Analysis of Cohen-Grossberg Neural Networks with Time Varying Delay[J]. Acta Electronica Sinica, 2008, 36(11): 2220-2223.
王占山, 张化光, 余 文, 等. 基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性[J]. 电子学报, 2008,36(11):2220-2223. DOI:
WANG Zhan-shan, ZHANG Hua-guang, YU Wen, et al. An LMI Approach to Robust Stability Analysis of Cohen-Grossberg Neural Networks with Time Varying Delay[J]. Acta Electronica Sinica, 2008, 36(11): 2220-2223. DOI:
研究了时变时滞Cohen-Grossberg神经网络的全局鲁棒稳定性问题.基于线性矩阵不等式技术
给出了保证时变时滞Cohen-Grossberg神经网络平衡点唯一性和全局鲁棒稳定性的新判据.这些新判据不依赖于时滞的大小和放大函数
且与现有的一些结果相比
具有易于验证、适用范围广、条件更不保守等特点.仿真结果验证了本文方法的有效性.
Robust stability problem for Cohen-Grossberg neural networks with time varying delay is investigated.Using linear matrix inequality technique
some new sufficient conditions guaranteeing the uniqueness and global robust stability of the equilibrium point of Cohen- Grossberg neural networks with time varying delay are derived
which are independent of the magnitude of time varying delay and amplification functions.Compared with some existing results
these new criteria are not conservative and are convenient to check.An example is used to show the effectiveness of the obtained results.
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