A robust circle criterion observer with application to neural mass models

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/232605

Title: A robust circle criterion observer with application to neural mass models
Author(s): Chong, Michelle; Postoyan, Romain; Nesic, Dragan; Kuhlmann, Levin; Varsavsky, Andrea
Abstract: A robust circle criterion observer is designed and applied to neural mass models. At present, no existing circle criterion observers apply to the considered models, i.e. the required linear matrix inequality is infeasible. Therefore, we generalise available results to derive a suitable estimation algorithm. Additionally, the design also takes into account input uncertainty and measurement noise. We show how to apply the observer to estimate the mean membrane potential of neuronal populations of a popular single cortical column model from the literature.
Publication type: Journal article
Source: Automatica, Vol. 48, no. 11 (Nov 2012), pp. 2986-2989
Publication year: 2012
FOR Code(s): 01 Mathematical Sciences; 08 Information and Computing Sciences; 09 Engineering
Keyword(s): Circle criterion; EEG; Electroencephalography; Neural models
Publisher: Elsevier
ISSN: 0005-1098
Publisher URL: http://dx.doi.org/10.1016/j.automatica.2012.08.008
Peer reviewed