Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Extraction of Specific Signals with Temporal Structure
Neural Computation
A Robust Extraction Algorithm Based on a Specific Kurtosis Value Range
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 01
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
Approach and applications of constrained ICA
IEEE Transactions on Neural Networks
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Fetal electrocardiogram (FECG) extraction is of vital importance in biomedical signal processing. A promising approach is blind source extraction (BSE) emerging from the neural network fields, which is generally implemented in a semi-blind way. In this paper, we propose a robust extraction algorithm that can extract the clear FECG as the first extracted signal. The algorithm exploits the fact that the FECG signal's kurtosis value lies in a specific range, while the kurtosis values of other unwanted signals do not belong to this range. Moreover, the algorithm is very robust to outliers and its robustness is theoretically analyzed and is confirmed by simulation. In addition, the algorithm can work well in some adverse situations when the kurtosis values of some source signals are very close to each other. The above reasons mean that the algorithm is an appealing method which obtains an accurate and reliable FECG.