A novel observer design method for neural mass models

doi:10.1088/1674-1056/24/9/090207

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.

Keywords: observer design neural mass model Lurie system theory

Received: 24 January 2015
Revised: 07 May 2015
Accepted manuscript online:

PACS:	02.30.Yy	(Control theory)
	87.19.le	(EEG and MEG)

Fund:

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

Corresponding Authors: Liu Xian
E-mail: liuxian@ysu.edu.cn

Cite this article:

Liu Xian (刘仙), Miao Dong-Kai (苗东凯), Gao Qing (高庆), Xu Shi-Yun (徐式蕴) A novel observer design method for neural mass models 2015 Chin. Phys. B 24 090207

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