Blind Separation of Non-Stationary Convoluted Mixtures Based on Time-Frequency Analysis

Abstract:

The signals of convoluted mixtures have a stated of non-stationary identity, and the change of their spectrum with time-varying usually could not be observed from the frequency domain, but they can be observed by the time-frequency method. Therefore, the blind separation of non-stationary convoluted mixtures based on time-frequency analysis is proposed in this paper. For the non-stationary identity, the space-albinism of the mixed matrices and the joint diagonalization of the time-frequency matrices are simulated to separate the convoluted mixtures. Two kinds of time-frequency analysis methods, Wigner-Ville distribution and improved Wigner-Ville distribution, are introduced, which are calculated with MATLAB 7.0 software. The simulated results show the improved Wigner-Ville distribution method has a better performance for blind separating of non-stationary convoluted and mixed signals.

• Periodical: Advanced Materials Research (Volumes 538-541)
• Pages: 2571-2575
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.538-541.2571
• Online since: June 2012
• Authors: Peng Wang, Ji Hua Cao, Xiao Chang Ni
• Keywords: Blind Source Separation (BSS), Convoluted Mixtures, Improved Wigner-Ville (IWVD), MATLAB 7.0, Time-Frequency Analysis, Wigner-Ville Distribution (WVD)

References

[1] S.Y. Low, S. Nordholm, and R. Togneri: IEEE Transactions on Speech and Audio Processing Vol. 12, No. 5 (2004), pp.1063-6676.

DOI: 10.1109/tsa.2004.832993

[2] Chitat Leung and Wanchi Siu: Signal Process 87(2007), pp.107-123.

[3] Abrar F and Deville Y : Signal Processing 85(2005), pp.1389-1403.

[4] Hongwei Lou and Guangrui Hu: Control and Decision (2004), pp.73-76.

[5] Hua Zhang: Harbin Industry University Publishing House(2007), pp.93-152.

[6] BONHOMME S and ROBIN J M : Journal of Econometrics(2009), pp.21-23.