A novel observer design method for neural mass models
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 s...
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| Published in | Chinese physics B Vol. 24; no. 9; pp. 68 - 72 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
01.09.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-1056 2058-3834 1741-4199 |
| DOI | 10.1088/1674-1056/24/9/090207 |
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| 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. |
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| AbstractList | 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. 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. |
| Author | 刘仙 苗东凯 高庆 徐式蕴 |
| AuthorAffiliation | Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering, . Yanshan University, Qinhuangdao 066004, China China Electric Power Research Institute, Beijing 100192, China |
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| CitedBy_id | crossref_primary_10_1016_j_irbm_2019_01_001 crossref_primary_10_1063_5_0020184 crossref_primary_10_1016_j_physa_2016_11_038 crossref_primary_10_3934_math_20241577 |
| Cites_doi | 10.1007/s11071-009-9539-3 10.1155/2014/215943 10.1016/j.physa.2007.05.030 10.1103/PhysRevE.90.032913 10.1103/PhysRevE.88.042905 10.1007/s11071-012-0638-1 10.1016/S0005-1098(00)00180-1 10.1155/2013/792507 10.1007/BF00199471 10.1007/s11571-014-9306-0 10.1109/TAC.2013.2294826 10.1016/S0167-6911(03)00170-1 10.1109/TBME.2014.2306424 10.1016/j.sysconle.2008.11.007 10.1016/j.neuroimage.2011.08.060 10.7551/mitpress/8436.001.0001 10.1137/1.9781611970777 10.1007/BF00270757 10.1007/s004220000160 10.1007/s10827-014-0517-5 10.1016/j.physa.2007.08.029 10.1109/TAC.2014.2310331 10.1002/rnc.1460 10.1016/j.neuroimage.2003.07.015 10.1016/j.automatica.2012.08.008 10.1016/j.neuropsychologia.2014.07.016 |
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| Notes | 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. observer design,neural mass model,Lurie system theory 11-5639/O4 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
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| References | Liu X (6) 2014; 23 22 23 24 25 26 27 28 29 Liu X (30) 2010; 20 Wang J (2) 2012; 21 31 Xu S Y (32) 2011; 20 10 11 12 13 14 15 16 18 19 Li L (1) 2011; 20 3 4 5 7 Liang H J (17) 2014; 23 8 9 Schiff S J (20) 2011 Leonov G A (21) 1996 |
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| Snippet | Neural mass models can simulate the generation of electroencephalography（EEG） signals with different rhythms,and therefore the observation of the states of... Neural mass models can simulate the generation of electroencephalography (EEG) signals with different rhythms, and therefore the observation of the states of... |
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| SubjectTerms | Brain Computer simulation Convergence Design engineering Dynamical systems Electroencephalography Errors Lurie型 Lurie系统 Mathematical models 数值模拟 神经网络观测器 系统理论 设计方法 质量模型 非线性系统 |
| Title | A novel observer design method for neural mass models |
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