On the selection of Intrinsic Mode Function in EMD method: Application on heart sound signal
On the selection of Intrinsic Mode Function in EMD method: Application on heart sound signal
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DOI：
10.1109/isabel.2010.5702895
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发表时间：
2010-11
期刊：
影响因子：
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通讯作者：
D. Boutana;M. Benidir;B. Barkat
中科院分区：
文献类型：
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作者：
D. Boutana;M. Benidir;B. Barkat
经验模式分解（EMD）允许将观测到的多分量信号分解成一组称为本征模式函数（IMF）的单分量信号。经验模态分解提供了大量的IMF，选择基本的IMF并消除冗余的IMF是重要的。本文提出了一种新的标准，同时基于Minkowski距离和α阶詹森雷尼发散（α-JRD），在一组提取的IMF中自动选择合适的IMF。使用合成和现实生活中的心音信号的例子，提出了为了验证所提出的技术的性能。
Empirical mode decomposition (EMD) allows decomposing an observed multicomponent signal into a set of monocomponent signals called Intrinsic Mode Functions (IMFs). EMD provides a large number of IMFs and it is important to select the fundamental IMFs and eliminate the redundant ones. This paper proposes a new criterion, based simultaneously on the Minkowski distance and the Jensen Rényi divergence of order α (α-JRD), to automatically select the appropriate IMFs in a set of the extracted ones. Examples, using synthetic and real-life heart sound signals, are presented in order to validate the performance of the proposed technique.