A novel observer design method for neural mass models  

作　　者：刘仙 苗东凯 高庆 徐式蕴 

机构地区：[1]Key Laboratory of Industrial Computer Control Engineering of Hebei Province,Institute of Electrical Engineering,Yanshan University [2]China Electric Power Research Institute

出　　处：《Chinese Physics B》2015年第9期68-72,共5页中国物理B（英文版）

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

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.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.

关 键 词：observer design neural mass model Lurie system theory 

分 类 号：R741.04[医药卫生—神经病学与精神病学] TN911.6[医药卫生—临床医学]