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 

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

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      码：68-72页

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.

主 题 词：observer design neural mass model Lurie system theory 

学科分类：1002[医学-临床医学类] 08[工学] 080401[080401] 0804[工学-材料学] 080402[080402] 0805[工学-能源动力学] 0704[理学-天文学类] 100204[100204] 10[医学] 

核心收录：

D　O　I：10.1088/1674-1056/24/9/090207

馆 藏 号：203428444...