A novel observer design method for neural mass models

作     者：刘仙 苗东凯 高庆 徐式蕴 

作者机构：Key Laboratory of Industrial Computer Control Engineering of Hebei ProvinceInstitute of Electrical EngineeringYanshan University China Electric Power Research Institute 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2015年第24卷第9期

页      面：68-72页

核心收录：

学科分类：1002[医学-临床医学] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 100204[医学-神经病学] 10[医学] 

基　　金：Project supported by the National Natural Science Foundation of China(Grant Nos.61473245 61004050 and 51207144) 

主　　题：observer design neural mass model Lurie system theory 

摘      要：Neural mass models can simulate the generation of electroencephalography（EEG） signals with different rhythms,and therefore the observation of the states of these models plays a significant role in brain research. The structure of neural mass models is special in that they can be expressed as Lurie systems. The developed techniques in Lurie system theory are applicable to these models. We here provide a new observer design method for neural mass models by transforming these models and the corresponding error systems into nonlinear systems with Lurie form. The purpose is to establish appropriate conditions which ensure the convergence of the estimation error. The effectiveness of the proposed method is illustrated by numerical simulations.