Abstract
Estimate the number of source signals is a necessary prerequisite for underdetermined blind sources separation (UBSS). The accuracy of sources number estimation has influence to the correctness of the sources separation. For this, a new algorithm—Hough-Windowed is proposed based on the assumption that the source signals are sparse. First, the algorithm constructs straight line equations of the observed signals based on Hough transformation. In order to obtain cluster areas, histogram is cumulated by windowed in transform domain. Then estimate the maximum of every cluster area. The number of different maximum is the number of source signals. Simulation results show the validity and expansibility of the algorithm. At the same time, compared with Potential function, the algorithm reflects the better noise immunity and the lower sparse sensitivity.
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Acknowledgments
The authors would like to thank for the projects supported by National Natural Science Foundation of China (Grant No. 61172038 and 60831001).
Thanks should also be given to the EMC Laboratory of Beijing University of Aeronautics and Astronautics, which provides a good environment and convenient conditions for this research.
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© 2013 Springer-Verlag Berlin Heidelberg
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Guo, H., Fu, Yq., Liu, Y., Wang, Jq. (2013). Methods for Source Number Estimation in Underdetermined Blind Sources Separation. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34528-9_44
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DOI: https://doi.org/10.1007/978-3-642-34528-9_44
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