动力系统实测数据的非线性混沌特性的判定<sup>*</sup>

马军海; 陈予恕; 刘曾荣

动力系统实测数据的非线性混沌特性的判定^*

1.
东南大学管理学院系统工程研究所, 南京 210018;
2.
天津大学力学系, 天津 300072;
3.
上海大学数学系, 上海 201800

基金项目: * 国家自然科学基金资助项目(19672043)

详细信息

中图分类号: O241;O175
计量
- 文章访问数: 2284
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- 被引次数: 0
出版历程
- 收稿日期: 1996-09-20
- 修回日期: 1998-03-01
- 刊出日期: 1998-06-15

Threshold Value for Diagnosis of Chaotic Nature of the Data Obtained in Nonlinear Dynamic Analysis

1.
Institute of Systems Engineering, Southeast University, Nanjing 210018, P. R. China;
2.
Department of Mechanics, Tianjing University, Tianjing 300072, P. R. China;
3.
Department of Mathematics, Shanghai Universtiy, Shanghai 201800, P. R. China

摘要

摘要: 本文利用相位随机化的替代数据方法,给出了一个对动力系统实测时间序列数据的特性进行判定的方法计算结果表明:相位的充分随机化可提高判别的准确程度把此判据用于随机时序与非线性混沌时序所得的判据值有明显的差异.
- 非线性混沌时序 /
- 替代数据 /
- 判据 /
- 随机时序
Abstract: In this paper surrogate data method of phase-randomized is proposed to identify the random or chaotic nature of the date obtained in dynamic analysis. The calculating results validate the phase-randomized method to be useful as it can increase the extent of accuracy of the results. And the calculating results show that threshold values of the random timeseries and nonlinear chaotic timeseries have marked difference.
- chaotic timeseries /
- surrogate-data /
- threshold value /
- random timeseries

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参考文献(18)

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