Blind Estimation of Evoked Potentials in Alpha Stable Distribution Environments

Evoked potentials (EPs) have been widely used to quantify neurological system properties. Traditional EP analyses are developed under the condition that the background noise in EP analysis are Gaussian distributed. Alpha stable distribution, a generalization of Gaussian, is better for modeling impulsive noise than Gaussian distribution in biomedical signal processing. Conventional blind separation and estimation method of evoked potentials is based on second order statistics (SOS). In this paper, we modify our conventional algorithms and analyze the stability and convergence performance s of the new algorithm. The simulation experiments show that the proposed algorithm based on fractional lower order statistics is more robust than the conventional algorithm based on second order statistics