Bivariate Empirical Mode Decomposition for Unbalanced Real-World Signals
Bivariate Empirical Mode Decomposition for Unbalanced Real-World Signals
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DOI：
10.1109/lsp.2013.2242062
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发表时间：
2013-01
影响因子：
3.9
通讯作者：
Alireza Ahrabian;N. Rehman;D. Mandic
中科院分区：
文献类型：
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作者：
Alireza Ahrabian;N. Rehman;D. Mandic
二元经验模态分解（BEMD）算法采用在圆上均匀采样，在多个方向上进行投影，从而计算二元信号的局部均值。然而，这种方法仅适用于双变量信号中两个数据通道的功率相等的情况，并且导致数据通道表现出功率不平衡的次优性能，这是实践中的典型情况。为此，我们利用二阶二元统计特性引入了一种非均匀采样方案，用于数据自适应选择投影方向。这样，对于相同数量的投影，得到的非均匀采样BEMD （NS-BEMD）算法提供了比标准BEMD更精确的双变量数据时频表示。在相关数据信道的BEMD、噪声辅助BEMD中最佳噪声功率的选择以及多普勒雷达速度估计的实例研究中，证明了该方法的优点。
The bivariate empirical mode decomposition (BEMD) algorithm employs uniform sampling on a circle to perform projections in multiple directions, in order to calculate the local mean of a bivariate signal. However, this approach is adequate only for equal powers in both the data channels within a bivariate signal, and results in suboptimal performance for data channels exhibiting power imbalance, a typical case in practice. To that end, we exploit second-order bivariate statistical properties to introduce a nonuniform sampling scheme for data adaptive selection of the projection directions. In this way, the resulting nonuniformly sampled BEMD (NS-BEMD) algorithm provides a more accurate time-frequency representation of bivariate data than standard BEMD, for the same number of projections. The advantages of the proposed approach are demonstrated in case studies on BEMD for correlated data channels, selection of optimal noise power in noise-assisted BEMD, and for speed estimation using Doppler radar.