Abstract
In this paper, we propose a new method for the blind source separation with assuming that the source signals are cyclostationarity. The proposed method exploits the characteristics of cyclostationary signals in the Fraction-of-Time probability framework in order to simultaneously separate all sources without restricting the distribution or the number of cycle frequencies of each source. Furthermore, a new identifiability condition is also provided to show which kind of cyclostationary source can be separated by the second-order cyclostationarity statistics. Numerical simulations are presented to demonstrate the effectiveness of the proposed approach.
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Cheviet, N.A., El Badaoui, M., Belouchrani, A., Guillet, F. (2009). Blind Separation of Cyclostationary Signals. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_4
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DOI: https://doi.org/10.1007/978-3-642-00599-2_4
Publisher Name: Springer, Berlin, Heidelberg
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