基于内模自适应估计器的VEP信号提取新方法  

A NOVEL VEP ESTIMATION METHOD BASED ON INTERNAL MODEL ADAPTIVE ESTIMATOR

作　　者：张建华[1] 曾衍钧[1] 徐宁寿[2] 

机构地区：[1]北京工业大学生物医学工程中心,北京100022 [2]北京工业大学电子信息与控制工程学院,北京100022

出　　处：《中国生物医学工程学报》2003年第1期30-36,共7页Chinese Journal of Biomedical Engineering

基　　金：北京市自然科学基金项目资助 ( 3982 0 0 6 )

摘　　要：本文基于确定性信号和扰动的内模建立了两种视觉诱发脑电 (VEP)和自发脑电 (EEG)混合信号的组合状态空间模型 ,基于时域参数模型提出了采用迭代型推广卡尔曼滤波算法来实现VEP信号的自适应估计 ,最后通过临床实际应用比较分析了两种建模方法的滤波性能。Based on the conceptual framework of internal models of the deterministic signal and disturbance, two types of composite state-space model, of the mixture of the visual evoked potential (VEP) with residual Electro-encephalogram (EEG) were derived. Based on the two time-domain parametric models, the adaptive estimation of the VEP signal was realized by using the iterative solution of extended Kalman filter. The filtering performance using each model was then compared and analyzed through extensive clinical applications.

关 键 词：视觉诱发脑电信号 迭代型 推广卡尔曼滤波算法 内模自适应卡尔曼滤法 

分 类 号：R741.044[医药卫生—神经病学与精神病学]