中国物理B ›› 2015, Vol. 24 ›› Issue (9): 90207-090207.doi: 10.1088/1674-1056/24/9/090207

• GENERAL • 上一篇    下一篇

A novel observer design method for neural mass models

刘仙a, 苗东凯a, 高庆a, 徐式蕴b   

  1. a Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
    b China Electric Power Research Institute, Beijing 100192, China
  • 收稿日期:2015-01-24 修回日期:2015-05-07 出版日期:2015-09-05 发布日期:2015-09-05
  • 基金资助:

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

A novel observer design method for neural mass models

Liu Xian (刘仙)a, Miao Dong-Kai (苗东凯)a, Gao Qing (高庆)a, Xu Shi-Yun (徐式蕴)b   

  1. a Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
    b China Electric Power Research Institute, Beijing 100192, China
  • Received:2015-01-24 Revised:2015-05-07 Online:2015-09-05 Published:2015-09-05
  • Contact: Liu Xian E-mail:liuxian@ysu.edu.cn
  • Supported by:

    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.

关键词: observer design, neural mass model, Lurie system theory

Abstract:

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.

Key words: observer design, neural mass model, Lurie system theory

中图分类号:  (Control theory)

  • 02.30.Yy
87.19.le (EEG and MEG)