Empirical Mode Decomposition for Trivariate Signals
Empirical Mode Decomposition for Trivariate Signals
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DOI：
10.1109/tsp.2009.2033730
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发表时间：
2010-03-01
影响因子：
5.4
通讯作者：
Mandic, Danilo P.
中科院分区：
文献类型：
--
作者：
ur Rehman, Naveed;Mandic, Danilo P.
提出了经验模式分解（EMD）的扩展，以使其适合在三变形信号上操作。通过使用四维旋转属性在三维空间中沿多个方向进行投影，对输入信号的局部平均信封的估计是EMD中的关键步骤。因此，提出的算法提取了嵌入信号中的旋转组件，并通过Hilbert-huang变换执行了准确的时频分析。关于合成三大点过程和现实世界三维信号的仿真支持该分析。
An extension of empirical mode decomposition (EMD) is proposed in order to make it suitable for operation on trivariate signals. Estimation of local mean envelope of the input signal, a critical step in EMD, is performed by taking projections along multiple directions in three-dimensional spaces using the rotation property of quaternions. The proposed algorithm thus extracts rotating components embedded within the signal and performs accurate time-frequency analysis, via the Hilbert-Huang transform. Simulations on synthetic trivariate point processes and real-world three-dimensional signals support the analysis.