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EMD新算法及其应用
引用本文:刘霖雯,刘超,江成顺. EMD新算法及其应用[J]. 系统仿真学报, 2007, 19(2): 446-447,464
作者姓名:刘霖雯  刘超  江成顺
作者单位:信息工程大学信息工程学院,河南郑州,450002
基金项目:国家自然科学基金;河南省高校杰出科研创新人才工程项目
摘    要:经验模态分解(ENID)算法是Hilbert-Huang变换(HHT)的核心算法,它的分解效果依赖于包络线的生成算法和端点延拓算法。采用分段幂函数插值算法求包络成。结合一种改进的端点延拓算法。得到了一种新的EMD算法。分析了分段幂函数插值算法的收敛精度。从数学角度解释了选取该插值算法的原因.最后,结合一个股票模型的仿真结果说明新的EMD算法效果更好。

关 键 词:HHT算法  EMD分解  信号处理  插值算法
文章编号:1004-731X(2007)02-0446-02
收稿时间:2005-10-24
修稿时间:2005-10-242006-02-21

Novel EMD Algorithm and Its Application
LIU Lin-wen,LIU Chao,JIANG Cheng-shun. Novel EMD Algorithm and Its Application[J]. Journal of System Simulation, 2007, 19(2): 446-447,464
Authors:LIU Lin-wen  LIU Chao  JIANG Cheng-shun
Affiliation:Institute of Information Engineering, Information Engineering University, Zhengzhou 450002, China
Abstract:Empirical mode decomposition (EMD), the core of Hilbert-Huang transformation, is reckoned on the algorithm of the extrama extending and generation of envelope curves. With the piecewise power function and an improved algorithm of extrama extending, a novel EMD algorithm was proposed. An error estimation of the piecewise power function interpolation was proposed to show the advantage of this algorithm. At last, a simulation on a stock model is presented to show that this novel EMD algorithm is more applicable to analyze the nonlinear and non-stationary signal than the previous EMD algorithm.
Keywords:HHT algorithm   EMD decomposition   signal processing   interpolation algorithm
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