A Robust Extraction Algorithm Based on a Specific Kurtosis Value Range
A Robust Extraction Algorithm Based on a Specific Kurtosis Value Range
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DOI：
10.1109/icnc.2007.131
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发表时间：
2007-08
期刊：
影响因子：
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通讯作者：
Yalan Ye;Zhi-Lin Zhang;Jia Chen;D. Wu
中科院分区：
文献类型：
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作者：
Yalan Ye;Zhi-Lin Zhang;Jia Chen;D. Wu
独立分量分析（伊卡）、盲源分离（BSS）以及盲源提取（BSE）等相关方法已被认为是神经网络和信号处理领域的基本数据分析工具。在本文中，我们提出了一种鲁棒算法的基础上，一个特定的峰度值范围，可以提取所需的源信号作为第一个输出信号与特定的峰度值范围。也就是说，如果我们知道期望信号的峰度值一般位于一个特定的范围内，而其他不需要的源信号的值不属于这个范围，我们可以使用所提出的算法成功地提取出期望信号。此外，该算法可以很好地工作在一些不良的情况下（当一些源信号的峰度值非常接近彼此）。此外，由于采用了内点罚函数法，该算法对峰度值范围的估计误差具有较强的鲁棒性。最后，我们使用所提出的算法提取准确可靠的胎儿心电图（FECG）。
Independent component analysis (ICA), blind source separation (BSS) and related methods like blind source extraction (BSE) have been considered as a fundamental data analysis tool in the fields of neural network and signal processing. In this paper, we propose a robust algorithm based on a specific kurtosis value range that can extract a desired source signal as the first output signal with a specific kurtosis value range. That is to say, if we know that the kurtosis value of the desired signal generally lies in a specific range, while the values of other unwanted source signals do not belong to this range, we can use the proposed algorithm to extract the desired signal successfully. Moreover, the algorithm can work well in some poor situation (when the kurtosis values of some source signals are very close to each other). In addition, because of adopting an interior point penalty function method, the algorithm is robust to the estimation error of the kurtosis value range. Finally, we use the proposed algorithm to extract the accurate and reliable fetal electrocardiogram (FECG).