| 不确定双向联想记忆神经网络的稳定性分析 |
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| 引用本文： | 关焕新,王占山,张化光.不确定双向联想记忆神经网络的稳定性分析[J].控制理论与应用,2008,25(3):421-426. |
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| 作者姓名： | 关焕新 王占山 张化光 |
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| 作者单位： | 1. 东北大学信息科学与工程学院,辽宁,沈阳,110004;沈阳工程学院继续教育部,辽宁,沈阳,110034
2. 东北大学信息科学与工程学院,辽宁,沈阳,110004 |
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| 基金项目： | 国家自然科学基金，辽宁省自然科学基金，东北大学博士后资助项目 |
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| 摘 要： | 对双向联想记忆神经网络研究了平衡点的鲁棒稳定性.该网络的参数不确定,并且有时变时滞.当神经网络的激励函数满足Lipschitz连续性条件时,通过选取合适的Lyapunov-Krasovskii函数,建立了两个全局鲁棒稳定判据.由于这些判据考虑了神经元激励作用和抑制作用对网络的影响,他们和时变时滞的数值无关,并且易于使用内点算法进行检验.在注释中和已有的结果进行了对比.两个数值例子展示了所得结果的有效性.
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| 关 键 词： | 双向联想记忆神经网络 时变时滞 不确定性 鲁棒稳定 线性矩阵不等式 Lyapunov-Krasovskii函数 |
| 收稿时间： | 9/7/2006 12:00:00 AM |
| 修稿时间： | 5/9/2007 12:00:00 AM |
Stability analysis of uncertain bi-directional associative memory neural networks with variable delays |
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| GUAN Huan-xin,WANG Zhan-shan and ZHANG Hua-guang.Stability analysis of uncertain bi-directional associative memory neural networks with variable delays[J].Control Theory & Applications,2008,25(3):421-426. |
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| Authors: | GUAN Huan-xin WANG Zhan-shan and ZHANG Hua-guang |
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| Affiliation: | School of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110004, China; Department of Continuous Education, Shenyang Institute of Engineering, Shenyang Liaoning 110034, China;School of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110004, China;School of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110004, China |
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| Abstract: | The robust stability of equilibrium point is studied for bi-directional associative memory neural networks with parameter uncertainties and time-varying delays.When the activation function satisfies the condition of Lipschitz continuity,two sufficient conditions are established for the globally robust stability of the equilibrium point by suitably choosing Lyapunov-Krasovskii functional.The obtained results,which take account of the effects of neural inhibitory and excitatory on neural networks,are independent of the sizes of the time-varying delays and are easy to be checked by the interior-point algorithms in MATLAB toolbox.They are compared with prior results in a remark,and are demonstrated by two numerical examples for their effectiveness. |
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| Keywords: | bi-directional associative memory neural networks time varying delays uncertainty robust stability linear matrix inequality(LMI) Lyapunov-Krasovskii functional |
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