| 引用本文: | 陈从颜, 宋文忠.一类二阶时延神经网络的分岔分析和控制[J].控制理论与应用,2003,20(1):45~48.[点击复制] |
| CHEN Cong-yan, SONG Wen-zhong.Bifurcation analysis and control of delayed neural network model with two-neurons[J].Control Theory and Technology,2003,20(1):45~48.[点击复制] |
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| 一类二阶时延神经网络的分岔分析和控制 |
| Bifurcation analysis and control of delayed neural network model with two-neurons |
| 摘要点击 1393 全文点击 975 投稿时间：2000-06-20 修订日期：2001-05-28 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.1.009 |
| 2003,20(1):45-48 |
| 中文关键词 时延神经网络 分岔控制 极限环控制 |
| 英文关键词 time delay neural networks bifurcation control amplitude control |
| 基金项目 |
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| 中文摘要 |
| 讨论了一类二阶时延网络系统的非线性特性,应用线性化稳定性和分岔理论,提出了该系统从稳定到分岔的条件.结论指出利用延迟时间可以进行分岔控制、极限环幅值控制等,并给出了仿真的具体实例. |
| 英文摘要 |
| The nonlinear behavior in a delayed neural network model with two neurons is investigated. Conditions from stability to bifurcation of the model are presented by applying the linear stability theory. The analytical mechanism for the beginning of cyclic behavior is based on a Hopf-type bifurcation theory. The bifurcation and amplitude of the bifurcated solution are proved to be controlled by utilizing bifurcation stability conefficients can control bifurcation. An example is given and numerical simulations are performed to illustrate the results. |