A robust nonlinear observer for a class of neural mass models.
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.
Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
Xian
0000-0003-0075-0824
X
Liu
Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
Dongkai
D
Miao
Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
Qing
0000-0001-6983-2305
Q
Gao
D000465:Algorithms; D003198:Computer Simulation; D004569:Electroencephalography; D006801:Humans; D008962:Models, Theoretical; D009422:Nervous System Diseases / Q000175:diagnosis; D017711:Nonlinear Dynamics