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Y. J. Shen and S. P. Yang, “A new Blind-Source-Separation method and its application to fault diagnosis of rolling bearing,” International Journal of Nonlinear Sciences and Numerical Simulation, Vol. 7, No. 3, pp. 245–250, 2006.

has been cited by the following article:

• TITLE: Research on Blind Source Separation for Machine Vibrations

  AUTHORS: Weiguo HUANG, Shuyou WU, Fangrang KONG, Qiang WU

  KEYWORDS: Blind Source Separation, Independent Component Analysis, Convolutive Mixtures, Machine Vibration, Residual Cross-Talking Error

  JOURNAL NAME: Wireless Sensor Network, Vol.1 No.5, December 16, 2009

  ABSTRACT: Blind source separation is a signal processing method based on independent component analysis, its aim is to separate the source signals from a set of observations (output of sensors) by assuming the source signals independently. This paper reviews the general concept of BSS firstly; especially the theory for convolutive mixtures, the model of convolutive mixture and two deconvolution structures, then adopts a BSS algorithm for convolutive mixtures based on residual cross-talking error threshold control criteria, the simulation testing points out good performance for simulated mixtures.