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The Scientific World Journal
Volume 2014 (2014), Article ID 215943, 5 pages
Research Article

A Robust Nonlinear Observer for a Class of Neural Mass Models

Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

Received 12 November 2013; Accepted 31 January 2014; Published 20 March 2014

Academic Editors: G. Cheron and X. Fan

Copyright © 2014 Xian Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new method of designing a robust nonlinear observer is presented for a class of neural mass models by using the Lur’e system theory and the projection lemma. The observer is robust towards input uncertainty and measurement noise. It is applied to estimate the unmeasured membrane potential of neural populations from the electroencephalogram (EEG) produced by the neural mass models. An illustrative example shows the effectiveness of the proposed method.