非高斯噪声下基于MD准则与Givens旋转的EP信号提取方法

Estimation of Evoked Potentials Based on MD Criterion and Givens Matrix in Non-Gaussian Noise Environments

传统的诱发电位(EP)提取与分离方法中,通常认为EP信号中混入的自发脑电(EEG)等噪声属于高斯分布。近年来一些研究表明了EEG信号具有一定的非高斯特性。α-稳定分布可以更好地描述实际应用中所遇到的具有显著脉冲特性的EEG噪声。本文提出一种适用于EP信号分离提取的基于最小分散系数准则与旋转变换的算法。计算机模拟和分析表明,在分数低阶稳定分布背景噪声条件下,这种算法是一种具有良好韧性的EP信号分离提取方法。

Traditional EP analysis is 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 processing. Conventional blind separation and estimation 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 Givens matrix. The simulation experiments show that the proposed new algorithm is more robust than the conventional algorithm.