从混沌信号中识别振荡分量的一种算法

AN ALGORITHM FOR THE IDENTIFICATION OF OSCILLATORY COMPONENTS IN CHAOTIC SIGNALS

  • 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%。

     

    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.

     

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