Blind Second-Order Source Extraction of Instantaneous Noisy Mixtures

The problem of blind source extraction (BSE) for noisy measurements is addressed in the domain of second-order statistics using the linear predictor method. By extending the results from the noise-free case, two methods for the noisy case are proposed, whereby, for rigor, the effect of noise is removed from the cost function. The so introduced algorithms are based, respectively, on the minimization of the normalized mean square prediction error (MSPE), and the minimization of MPSE. The analysis of the derived BSE algorithms is supported by simulations

[1]  Wei Liu,et al.  A normalised kurtosis-based algorithm for blind source extraction from noisy measurements , 2006, Signal Process..

[2]  Jun Wang,et al.  Sequential blind extraction of instantaneously mixed sources , 2002, IEEE Trans. Signal Process..

[3]  Andrzej Cichocki,et al.  On-line Algorithm for Blind Signal Extraction of Arbitrarily Distributed, but Temporally Correlated Sources Using Second Order Statistics , 2000, Neural Processing Letters.

[4]  Andrzej Cichocki,et al.  Adaptive blind signal and image processing , 2002 .

[5]  Danilo P. Mandic,et al.  AN ONLINE ALGORITHM FOR BLIND EXTRACTION OF SOURCES WITH DIFFERENT DYNAMICAL STRUCTURES , 2003 .

[6]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

[7]  Shun-ichi Amari,et al.  Sequential blind signal extraction in order specified by stochastic properties , 1997 .

[8]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[9]  Andrzej Cichocki,et al.  Blind signal extraction of signals with specified frequency band , 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

[10]  D. Chakrabarti,et al.  A fast fixed - point algorithm for independent component analysis , 1997 .

[11]  Wei Liu,et al.  A class of novel blind source extraction algorithms based on a linear predictor , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[12]  Allan Kardec Barros,et al.  Extraction of Specific Signals with Temporal Structure , 2001, Neural Computation.

[13]  Simon Haykin,et al.  Adaptive filter theory (2nd ed.) , 1991 .

[14]  S. Haykin.  Unsupervised adaptive filtering, vol. 1: Blind source separation , 2000 .