A robust extraction algorithm for biomedical signals from noisy mixtures

Yongjian ZHAO, Boqiang LIU, Sen WANG

Front. Comput. Sci. ›› 0

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PDF(218 KB)
Front. Comput. Sci. ›› DOI: 10.1007/s11704-011-1043-5
RESEARCH ARTICLE

A robust extraction algorithm for biomedical signals from noisy mixtures

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Abstract

Blind source extraction (BSE) is widely used to solve signal mixture problems where there are only a few desired signals. To improve signal extraction performance and expand its application, we develop an adaptive BSE algorithm with an additive noise model. We first present an improved normalized kurtosis as an objective function, which caters for the effect of noise. By combining the objective function and Lagrange multiplier method, we further propose a robust algorithm that can extract the desired signal as the first output signal. Simulations on both synthetic and real biomedical signals demonstrate that such combination improves the extraction performance and has better robustness to the estimation error of normalized kurtosis value in the presence of noise.

Keywords

blind source extraction (BSE) / normalized kurtosis / objective function / biomedical signal / Lagrange multiplier method

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Yongjian ZHAO, Boqiang LIU, Sen WANG. A robust extraction algorithm for biomedical signals from noisy mixtures. Front Comput Sci Chin, https://doi.org/10.1007/s11704-011-1043-5

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