中文说明：
鉴于LCD方法存在的问题，本文提出了一种基于互相关匹配端点延拓局部特征尺度分解（Cross-correlation matching endpoint Extension Local Characteristic scale Decomposition，简称CELCD），由于LCD分解原理是依据信号的局部极值点信息不断进行筛分信号，在信号分解时需要先确定信号的局部极值点，而信号的两个端点可能不是极值点，因此在信号两端点就会出现虚假成分，且该现象随着分解的进行向数据内部扩散，产生端点效应，导致分解结果失真。而CELCD方法的本质在于探索待分解信号前后端的数据规律，延长波形，使得端点效应不出现在原始信号分解的片段上，从而消除端点效应。
English Description：
In view of the problems of LCD method, this paper proposes a cross correlation matching endpoint extension local characteristic scale based on cross correlation matching Because the decomposition principle of LCD is based on the local extremum information of the signal to continuously screen the signal, it is necessary to determine the local extremum of the signal when decomposing the signal, and the two endpoints of the signal may not be extremum points, so there will be false components at the two ends of the signal, and this phenomenon will spread to the internal data with the decomposition process, resulting in endpoint The result of decomposition is distorted. The essence of celcd method is to explore the data law of the front and back end of the signal to be decomposed, extend the waveform, so that the end effect does not appear in the original signal decomposition segment, so as to eliminate the end effect.