李宗春, 邓勇, 张冠宇, 杨晓晖. 变形测量异常数据处理中小波变换最佳级数的确定[J]. 武汉大学学报 ( 信息科学版), 2011, 36(3): 285-288.
引用本文: 李宗春, 邓勇, 张冠宇, 杨晓晖. 变形测量异常数据处理中小波变换最佳级数的确定[J]. 武汉大学学报 ( 信息科学版), 2011, 36(3): 285-288.
LI Zongchun, DENG Yong, ZHANG Guanyu, YANG Xiaohui. Determination of Best Grading of Wavelet Transform in Deformation Measurement Data Filtering[J]. Geomatics and Information Science of Wuhan University, 2011, 36(3): 285-288.
Citation: LI Zongchun, DENG Yong, ZHANG Guanyu, YANG Xiaohui. Determination of Best Grading of Wavelet Transform in Deformation Measurement Data Filtering[J]. Geomatics and Information Science of Wuhan University, 2011, 36(3): 285-288.

变形测量异常数据处理中小波变换最佳级数的确定

Determination of Best Grading of Wavelet Transform in Deformation Measurement Data Filtering

  • 摘要: 综合分析数据去噪效果的4个分项评价指标,即数据的均方根差变化量、互相关系数、信噪比及平滑度,将各分项评价指标归化到0,1后相加得到总体评价指标,将总体评价指标最大值所对应的级数定义为小波分解与重构的最佳级数。模拟和实测两个算例验证了此方法的有效性。

     

    Abstract: Wavelet transform is widely used in deformation measurement data filtering,but there is still no definite solution to determine the best grading of its decomposition and reconstruction.Firstly,four parameters,the gap of mean square error variances between two adjacent gradings,correlation coefficient,signal-noise ratio and flatness,are integrated in as evaluation indexes.Then they are transformed to according to their contributions to the best grading.Finally,these four transformed parameters are added up to as a collective evaluation index,and the grading corresponding to the maximum value of the collective evaluation index is the best.Two examples,the one is a stimulant siginal,and the other is from actual deformation measurement,are used to test the new method,which prove the method is feasible and reliable.

     

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