A robust extraction algorithm for biomedical signals from noisy mixtures

Authors:
Yongjian Zhao;Boqiang Liu;Sen Wang
Affiliations:
School of Control Science and Engineering, Shandong University, Jinan, China 250061 and School of Information Engineering, Shandong University at Weihai, Weihai, China 264209;School of Control Science and Engineering, Shandong University, Jinan, China 250061;Kodak Research Laboratories, Eastman Kodak Company, Rochester, USA 14620
Venue:
Frontiers of Computer Science in China
Year:
2011

Citing 11
Cited 1

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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.