Improved EMD Based on Piecewise Cubic Hermite Interpolation and Mirror Extension

• 作 者: ZHANG Xuejun HUO Yan WAN Dongsheng
• 机 构: College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, N
• 出 处: 电子学报（英文）
• 发表日期: 2020年5期
• 关键词: Common spatial pattern EEG signal Empirical mode decomposition Feature extractio

This paper proposes an improved Empirical mode decomposition (EMD) method piecewise cubic hermite interpolation and mirror extension.Firstly,mirror expansion method is used to expand preliminary signal endpoint;then the piecewise cubic Hermite interpolation algorithm is applied to obtain the envelopes.Finally Intrinsic mode functions (IMFs) are obtained through improved EMD (MPC-HEMD).Through the analysis on simulation signals and Electroencephalogram (EEG) signals,we found that the new method was better than the traditional method.