用第二代小波去噪降低EMD边缘效应

应用经验模式分解（EMD）进行信号处理时通常利用三次样条插值拟合信号的上下包络，因而常出现边缘效应，影响处理质量。本文提出先用第二代小波对信号去噪，再运用EMD。第二代小波在保持第一代小波原有特性的基础上，可实现整数到整数的小波变换，并且转换速度更快，不需要额外的内存空间。仿真实验表明，同等条件下用第二代小波能有效减少EMD的分解层数，提高分解效率，同时能降低边界效应的影响，使EMD更具实际应用价值。

Reducing Edge Effect of EMD with Second Generation Wavelet Denoising

The traditional empirical mode decomposition(EMD) usually uses cubic spline interpolation to fit the upper and lower envelopes of the signal,leading to ill behavior on edges and therefore degrading the signal processing quality. We resolve the edge problem of EMD by using the second-generation wavelet denoise technique.Compared with the first generation wavelets,the second generation has lower computational complexity and less memory requirement.Numerical experiments show that the second-generation wavelet denoising can effectively reduce the edge effect with fewer decomposition layers,making EMD more practical.