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C. Jutten and J. Herault, “Blind separation of sources, Part 1: An adaptive algorithm based on neuromimetic structure,” Signal Processing, No. 24, pp. 1–10, 1991.

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.