EMD自适应三角波匹配延拓算法

波形匹配延拓是遏制经验模态分解（EMD）端点效应的有效方法，针对现有波形匹配延拓方法的不足，提出了一种自适应的三角波形匹配延拓方法，改进了三角波匹配度的计算方法和匹配子波的寻优算法。改进的三角波匹配度计算方法，突出延拓平顺性的同时，加强了端点处数据与内部波形的关联。自适应的匹配寻优算法，首先在固定极值点对应的波段内部搜寻局部最佳子波的截取时刻，截取局部最优匹配子波，然后在局部最优子波内搜寻全局最优匹配子波，提高了子波截取的合理性与匹配的准确性。仿真信号及实验信号分析表明，该方法可有效抑制EMD端点效应，显著提高分解精度。

A self-adaptive triangular waveform matching extension algorithm for EMD

Waveform matching extension is considered to be an effective method to improve the end effect of empirical mode decomposition (EMD). According to those deficiencies of existing matching extension methods, this paper proposes a self-adaptive triangular waveform matching extension method for EMD，which ameliorated both the matching degree algorithm of triangular waveform and the searching algorithm for optimal triangular waveform. The new matching degree algorithm not only promoted the extension’s smoothness but enhanced the relationship between the data near the end-point and waveform inside. By the new searching algorithm, we firstly searched for intercepting time to cut out the local optimal wavelet in each wave band corresponding to the fixed extreme point, and then searched for the global optimal wavelet in the local optimal wavelets. Based on the simulated signals and experimental signal analysis, it is suggested that the method could effectively mitigate the end effects of EMD and significantly improve the precision of decomposition.