Blind estimation of evoked potentials based on covariations in non-gaussian noise.
- Author:
Zhengjian LIN
1
;
Daifeng ZHA
;
Jian SHENG
Author Information
1. College of Electronic Engineering, Jiujiang University, Jiujiang 332005, China. lzjuestc@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artifacts;
Brain;
physiology;
Computer Simulation;
Electroencephalography;
methods;
Evoked Potentials;
physiology;
Humans;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2010;27(4):727-730
- CountryChina
- Language:Chinese
-
Abstract:
Evoked potentials (EPs) have been widely used to quantify neurological system properties. Traditional EP analysis has been developed under the condition that the background noises in EP are Gaussian distributed. Recently some researches indicate that electroencephalogram (EEG) is non-guassian in some especial conditions. Alpha stable distribution can model impulsive EEG in especial experimentation such as acceleration bump and devoid oxygen. In this paper, blind signals separation based on covariations is analyzed and discussed by the nonexistence of the finite second or higher order statistic. The simulation experimental results show that the method has good performance to separate Evoked potentials (EPs) from fractional lower order alpha stable distribution noise.
