Noisy component extraction with reference

Authors:
Yongjian Zhao;Hong He;Jianxun Mi
Affiliations:
School of Information Engineering, Shandong University, Weihai, China 264209;School of Information Engineering, Shandong University, Weihai, China 264209;Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China 518055 and Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China 5180 ...
Venue:
Frontiers of Computer Science: Selected Publications from Chinese Universities
Year:
2013

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Abstract

Blind source extraction (BSE) is particularly attractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of noise and can only work well in noise-free environments. In practice, the desired signal is often contaminated by additional noise. Therefore, we try to tackle the problem of noisy component extraction. The reference signal carries enough prior information to distinguish the desired signal from signal mixtures. According to the useful properties of Gaussian moments, we incorporate the reference signal into a negentropy objective function so as to guide the extraction process and develop an improved BSE method. Extensive computer simulations demonstrate its validity in the process of revealing the underlying desired signal.