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Proceedings Paper

A time-frequency algorithm for noisy BSS model
Author(s): Jing Guo; Xiao-Ping Zeng
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Paper Abstract

In most practical blind source separation (BSS) applications, the observations contain additive source noise that limits the performances of most existing BSS algorithms. In this paper, we propose a new BSS approach exploiting the difference in the time-frequency (t-f) signatures of these sources to be separated. The approach uses smooth pseudo Wigner-Ville distribution (SPWVD) to obtain t-f distribution, then localizes the signal energy by Hough transform and selects a set of spatial t-f points based on the dominant eigenvalue of SPWVD of observations. Finally, numerical performance simulations are provided highlighting its effectiveness.

Paper Details

Date Published: 1 October 2011
PDF: 8 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82853Z (1 October 2011); doi: 10.1117/12.913239
Show Author Affiliations
Jing Guo, Southwest Univ. Chongqing (China)
Xiao-Ping Zeng, Chongqing Univ. (China)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)

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