一种基于GEP的EMD端点效应抑制方法
中国测试杨 波, 李世平
 
摘  要:针对经验模态分解(EMD)在分解信号时存在的端点效应问题,为抑制端点效应对信号分析带来的影响,进一步提高EMD分解准确度,提出基于基因表达式编程(GEP)的EMD改进算法。通过仿真实验与镜像延拓等其他3种常用端点效应抑制方法作对比,并计算评价端点效应的两个指标,最后,通过这4种方法分别测量出原始信号的瞬时频率以作验证。仿真结果表明:基于GEP的EMD改进算法在分解信号后各分量两端发散程度最小,评价指标也均优于其他3种传统的改进方法,且更加准确地测量出原始信号的瞬时频率。证明该改进算法能更有效地抑制EMD端点效应,具有更高的应用价值。
关键词:经验模态分解;基因表达式编程;端点效应;瞬时频率
文献标志码:A       文章编号:1674-5124(2015)12-0032-04
GEP-based suppression of end effect in EMD 
YANG Bo, LI Shiping
(The Second Artillery Engineering College,Xi’an 710025,China)
Abstract: An improved algorithm of empirical mode decomposition (EMD) based on gene expression programming(GEP) was proposed in this paper to solve the end effect existing in the signal decomposition process of EMD and to restrain the strong impact brought of end effect on signal analysis to improve further the decomposition precision of EMD. After comparing it with three other commonly-used methods namely simulation and experiment and mirror extension, the two indicators of end effect were calculated and evaluated and the instantaneous frequency of original signals was measured and verified ultimately. The simulation results indicate that the divergence degree at both ends of each component is the lowest, the evaluation indicators are more superior, and the instantaneous frequency of the original signal measured is more precise compared with the three traditional improved methods. It has proven that this improved algorithm is more precise and practical in restraining the end effect.
Keywords: EMD; GEP; end effect; instantaneous frequency