Letters: Nonlinear innovation to blind source separation

Authors:
Zhenwei Shi;Changshui Zhang
Affiliations:
Image Processing Center, School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100083, PR China;State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, TNList, Department of Automation, Tsinghua University, Beijing 1000 ...
Venue:
Neurocomputing
Year:
2007

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Abstract

This letter proposes a blind source separation (BSS) method based on the nonlinear innovation of original sources. A simple algorithm is presented by minimizing a loss function of the nonlinear innovation. The method exploits the nonstationarity of sources in the sense that the variance of each source signal can be assumed to change smoothly as a function of time. Simulations verify the efficient implementation of the proposed method, especially its robustness to the outliers.