引用本文: | 朱训林,岳东.网络化神经网络的时滞依赖稳定性判据[J].控制理论与应用,2012,29(9):1169~1175.[点击复制] |
ZHU Xun-lin,YUE Dong.Delay-dependent stability criteria for network-based neural networks[J].Control Theory and Technology,2012,29(9):1169~1175.[点击复制] |
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网络化神经网络的时滞依赖稳定性判据 |
Delay-dependent stability criteria for network-based neural networks |
摘要点击 1991 全文点击 1190 投稿时间:2012-03-01 修订日期:2012-06-21 |
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DOI编号 10.7641/j.issn.1000-8152.2012.9.JCAC12036 |
2012,29(9):1169-1175 |
中文关键词 神经网络 采样控制 稳定性条件 |
英文关键词 neural networks (NNs) sampled-data control stability criteria |
基金项目 This work was supported by the National Nature Science Foundation of China (No. 61174085, 61074025, 60834002). |
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中文摘要 |
本文研究了网络化神经网络的稳定性问题. 首先, 为了利用网络系统的采样特征, 定义了一个新的Lyapunov泛函; 通过分析网络诱导时延和执行周期之间的关系, 采用一个迭代凸组合技术, 得到了一个包含较少保守性的稳定性判据. 然后, 给出一个基于采样数据的神经网络稳定性判据, 减少了计算复杂性. 最后, 通过一个数例, 验证了本文方法的有效性和优越性. |
英文摘要 |
This paper investigates the problem of stability of network-based neural networks (NNs). To exploit the sampling characteristic of network systems, we define a new type of Lyapunov functional. By analyzing the relation between the network-induced delay and the executive duration, and employing an iterative convex combination technique, we develop a less conservative stability criterion for network-based NNs. To reduce the computational complexity, we also propose a stability criterion for sampled-data-based NNs. An illustrative example is given to show the effectiveness and the advantages of the proposed method. |
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