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Juha Karhumen;Erkki Oja;Liuyue Wang;Ricardo Vigario;Jyrki Joutsensalo. (1997) A class of neural networks for independent component analysis. IEEE. Trans. on Neural Network,vol 8,No.3.

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• TITLE: New blind estimation method of evoked potentials based on minimum dispersion criterion and fractional lower order statistics

  AUTHORS: Daifeng Zha

  KEYWORDS: Evoked potentials (EPs), Alpha stable distribution, Blind source separation, Minimum dispersion (MD), Fractional lower order statistics (FLOS)

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.1 No.2, August 25, 2008

  ABSTRACT: Evoked potentials (EPs) have been widely used to quantify neurological system properties. Tra-ditional EP analysis methods are developed under the condition that the background noises in EP are Gaussian distributed. Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noises than Gaussian distribution in biomedical signal proc-essing. Conventional blind separation and es-timation method of evoked potentials is based on second order statistics or high order Statis-tics. Conventional blind separation and estima-tion method of evoked potentials is based on second order statistics (SOS). In this paper, we propose a new algorithm based on minimum dispersion criterion and fractional lower order statistics. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.