DTS-AMS型神经网络用于自发脑电信号残部的外推估计──提取视觉诱发脑电信号的新方法之二

基金项目:

北京市自然科基金资助项目(3982006)

详细信息

Extrapolation of the Electroencephalogram Residual Via DTS-AMS Type Neural Network

1. College of Electronic Information and Control Engineering, Beijing Polytechnic University, Beijing, 100022;
2. Department of Neural Internal Medicine, Beijing Friendship Hosptial, Beijing, 100050

摘要: 利用可实现对任意阶多元多项式超曲面的无差逼近的、基于离散泰勒级数的高阶联想记忆系统(DTS-AMS),对(本系列文章之一中所得)自发脑电(EEG)信号错相叠加平均后的残余信号进行建模和外推估计.数字仿真结果表明,此法通过十次左右的视觉刺激,即可将视觉诱发脑电(VEP)信号从EEG信号中分离出来,所得VEP信号潜伏期P₁₀₀精度可满足一般临床诊断要求.
- 信号估计 /
- 视觉诱发电位 /
- 脑电信号 /
- 人工神经网络 /
- 高阶联想记忆系统
Abstract: Utilizings the higher-oder associative memory system via discrete Talor series (DTS-AMS) which can make an error-free approximation to the multi-variable polynomial function with arbitrary order, this paper realizes the modeling and extrapolation of the EIectroencephalogram(EEG) residual signal obtained from the phase-shifting and superposition. Numerical simulation results have shown that, through about only 10 times of visual stimulation, the Visual Evoked Potential(VEP) can be extracted from the EEG background with a satisfactory identification accuracy of the latency parameter P100 for the clinical use.
- signal estimation /
- visual evoked potential /
- EEG /
- artifical neural network /
- higher-order associative memory system