作者：杨波, 李世平

作者单位：第二炮兵工程大学, 陕西 西安 710025

关键词：经验模态分解;基因表达式编程;端点效应;瞬时频率

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。

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

2015, 41(12): 32-35  收稿日期: 2015-06-05;收到修改稿日期: 2015-08-13

基金项目: 

作者简介: 杨波(1992-),男,江西南昌市人,硕士研究生,专业方向为控制科学与工程。

参考文献

[1] Huang N E. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proc R Soc Lond,1998(454):903-995.
[2] Huang N E. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis[J]. Proc R Soc Lond,2003(459):2317-2345.
[3] 刘慧婷,张旻,程家兴. 基于多项式拟合算法的EMD端点问题的处理[J]. 计算机工程与应用,2004,40(16):82-86.
[4] 方琨,王渝,马利兵,等. 基于RO-SBM 的Hilbert-Huang变换端点效应抑制方法[J]. 振动、测试与诊断,2013,33(2):319-324.
[5] Zhao J P, Huang D J. Mirror extending and circular spline function for empirical mode decomposition method[J]. Journal of Zhejiang University(SCIENCE),2001(2):247-252.
[6] Ferreira C. Gene expression programming: a new adaptive algorithm for solving problems[J]. Complex Systems,2001,13(2):87-129.
[7] Zuo J, Tang C J, Li, et al. Time series prediction based on gene expression programming[C]//Proceding of the 5th International Conference for Web Information Age 2004,LNCS 3129,Berlin:Springer-Verlag,2004:55-64.
[8] 唐常杰,张天庆,左杰,等. 基于基因表达式编程的知识发现[J]. 计算机应用,2004,24(10):7-10.
[9] 李建,刘伟,郭晓婷. 基于EMD分解的端点延拓新方法[J].电源技术,2012,36(10):1573-1575.
[10] 张贤达,保铮. 非平稳信号分析与处理[M]. 北京:国防工业出版社,1998:47.