| 引用本文: | 余昭旭, 吴惕华.一类时滞神经网络系统的指数稳定性[J].控制理论与应用,2005,22(2):321~324.[点击复制] |
| YU Zhao-xu, WU Ti-hua.On the exponential stability of neural networks systems with time delays[J].Control Theory and Technology,2005,22(2):321~324.[点击复制] |
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| 一类时滞神经网络系统的指数稳定性 |
| On the exponential stability of neural networks systems with time delays |
| 摘要点击 1364 全文点击 1034 投稿时间：2003-07-04 修订日期：2004-03-09 |
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| DOI编号 10.7641/j.issn.1000-8152.2005.2.030 |
| 2005,22(2):321-324 |
| 中文关键词 神经网络 时滞 指数稳定性 范数 矩阵测度 |
| 英文关键词 neural networks time delays exponential stability norm matrix measur |
| 基金项目 河北省自然科学基金资助项目(602623). |
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| 中文摘要 |
| 利用矩阵测度研究了一类时滞神经网络系统的指数稳定性,给出保证神经网络系统指数稳定的充分条件.输出函数不需要满足Lipschitz条件,且也不要求它们可微或严格单调递增.在关联矩阵不对称的情况下,所得到的结论仍然成立.最后一个数值例子验证了判据的有效性. |
| 英文摘要 |
| The exponential stability of Hopfield-type neural networks with time delays is analyzed by using the method of matrix measure,and sufficient conditions are obtained for general exponential stabilities.The system admits a unique equilibrium in which the output functions do not satisfy the Lipschitz conditions and neither requires them to be differential or strictly monotonously increasing.All the results still hold without assuming any symmetry of the connection matrix.Finally a numeric example is presented to verify the validity of these criteria. |