基于改进Cao算法确定奇异谱嵌入维数及应用

Determining the singular spectrum embedding dimension based on an improved Cao algorithm

针对奇异谱分析嵌入维数不确定性这一问题,以往学者的方法过于主观。文中基于Cao算法对其嵌入维数的选择进行研究,同时针对该算法存在的不足,提出改进Cao算法,在理论分析的基础上,用改进算法进行仿真实验,实验结果表明:改进的算法对嵌入维数的选择更具有准确性和高效性,减少了主观性。最后将其应用到变形监测数据,实现对监测数据的降噪处理,并提取主要趋势项。

According to the singular spectrum analysis for embedding dimension of uncertainty,the methods of the past scholars are too subjective.The choice of embedding dimension,based on Cao algorithm is analyzed.At the same time,it has improved the algorithm for the shortcomings of Cao algorithm.The improved algorithm simulation experiment results show that the improved algorithm used to select the embedding dimension is more accurate and efficient by reducing the subjectivity,based on the theoretical analysis.Finally this algorithm is applied to the deformation monitoring datas.The results realize the noise reduction of processing monitoring datas and extract the key trends items.