| 引用本文: | 张继业, 戴焕云, 邬平波.Hopfield神经网络系统的全局稳定性分析(英文)[J].控制理论与应用,2003,20(2):180~184.[点击复制] |
| ZHANG Ji-ye, DAI Huan-yun, WU Ping-bo-.Global stability analysis in Hopfield neural networks[J].Control Theory and Technology,2003,20(2):180~184.[点击复制] |
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| Hopfield神经网络系统的全局稳定性分析(英文) |
| Global stability analysis in Hopfield neural networks |
| 摘要点击 1423 全文点击 1178 投稿时间：2000-07-11 修订日期：2002-09-18 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.2.004 |
| 2003,20(2):180-184 |
| 中文关键词 神经网络 全局稳定性 M-矩阵 |
| 英文关键词 neural network global asymptotic stability M matrix |
| 基金项目 |
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| 中文摘要 |
| 研究一类Hopfield神经网络系统的平衡状态的存在性、唯一性与全局稳定性, 这类系统放弃了以前对激励函数的有界性、单调性和可微性要求. 利用M矩阵理论, 通过构造适当的Lyapunov函数, 得到了系统全局渐近稳定的充分条件. |
| 英文摘要 |
| The existence and uniqueness of the equilibrium and the global attractivity of Hopfield neural network models are investigated. Instead of assuming the boundedness, monotonicity and differentiability of the activation functions and by using M matrix theory, Lyapunov functions are constructed and employed to establish sufficient conditions for global asymptotic stability. |
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