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...

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Detalles Bibliográficos
Autores principales: Liu, Xian, Miao, Dongkai, Gao, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981059/
https://www.ncbi.nlm.nih.gov/pubmed/24790554
http://dx.doi.org/10.1155/2014/215943
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author Liu, Xian
Miao, Dongkai
Gao, Qing
author_facet Liu, Xian
Miao, Dongkai
Gao, Qing
author_sort Liu, Xian
collection PubMed
description 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.
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spelling pubmed-39810592014-04-30 A Robust Nonlinear Observer for a Class of Neural Mass Models Liu, Xian Miao, Dongkai Gao, Qing ScientificWorldJournal Research Article 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. Hindawi Publishing Corporation 2014-03-20 /pmc/articles/PMC3981059/ /pubmed/24790554 http://dx.doi.org/10.1155/2014/215943 Text en Copyright © 2014 Xian Liu et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Liu, Xian
Miao, Dongkai
Gao, Qing
A Robust Nonlinear Observer for a Class of Neural Mass Models
title A Robust Nonlinear Observer for a Class of Neural Mass Models
title_full A Robust Nonlinear Observer for a Class of Neural Mass Models
title_fullStr A Robust Nonlinear Observer for a Class of Neural Mass Models
title_full_unstemmed A Robust Nonlinear Observer for a Class of Neural Mass Models
title_short A Robust Nonlinear Observer for a Class of Neural Mass Models
title_sort robust nonlinear observer for a class of neural mass models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981059/
https://www.ncbi.nlm.nih.gov/pubmed/24790554
http://dx.doi.org/10.1155/2014/215943
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