计算物理 ›› 1997, Vol. 14 ›› Issue (S1): 592-594.
• 论文 • 上一篇 下一篇
刘健文, 董佩明, 李耀东, 王炳仁, 金维明
收稿日期:
修回日期:
出版日期:
发布日期:
Liu Jianwen, Dong Peiming, Li Yaodong, Wang Bingren, Jing Weiming
Received:
Revised:
Online:
Published:
摘要： 阐述了奇异谱分析方法的数学原理和分离振荡分量的重要性质。取100天的窗口长度研究我国东南地区地面气温序列,发现明显存在周期为35~40天和20天左右的主要低频振荡,相应频率段约占总方差的90%。
关键词: 混沌, 时间序列, 奇异谱分析
Abstract: The Singular Spectrum Analysis method,especially on the fundamental property of identifying the oscillatory compo-nents,is described.It is applied to a 30-year surface temperature series of east-southem china with a windows length of 100 days.Two main low-frequency oscillations with period of 35-40day and about 20 days are found to be robust,accounting for about 90% of total variance in the relevant frequency band.
Key words: chaos, time-series, singlar spectrum analysis
中图分类号:
P468
刘健文, 董佩明, 李耀东, 王炳仁, 金维明. 从混沌信号中识别振荡分量的一种算法[J]. 计算物理, 1997, 14(S1): 592-594.
Liu Jianwen, Dong Peiming, Li Yaodong, Wang Bingren, Jing Weiming. AN ALGORITHM FOR THE IDENTIFICATION OF OSCILLATORY COMPONENTS IN CHAOTIC SIGNALS[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 1997, 14(S1): 592-594.
0 / 推荐
导出引用管理器 EndNote|Ris|BibTeX
链接本文: http://www.cjcp.org.cn/CN/
http://www.cjcp.org.cn/CN/Y1997/V14/IS1/592
