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7 篇 会议

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检索条件"主题词=Multidimensional support vector regression"

共 7 条记录，以下是1-10 订阅

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EEG source localization of ERP based on multidimensional support vector regression approach

EEG source localization of ERP based on multidimensional sup...

引用

7th International Conference on Machine Learning and Cybernetics

作者： Li, Jian-Wei Wang, You-Hua Wu, Qing Wei, Yu-Fang An, Jin-Long Hebei Univ Technol Sch Comp Sci & Software Tianjin 300130 Peoples R China Hebei Univ Technol Sch Elect Engn & Automat Tianjin 300130 Peoples R China

ISBN: (纸本)9781424420957

A new integrated multi-method system is presented to estimate the location and moment of equivalent current dipole sources of event-related potentials (ERP). In order to handle the large-scale high dimension problems efficiently and quickly, the ISOMAP algorithm was used to find the low dimensional manifolds from recorded EEG. Then, based on reduced dimension data, multidimensional support vector regression (MSVR) with similar iterative re-weight least square (IRWLS) was used to discover the relationship between the observation potentials on the scalp and the internal sources within the brain. In our experiments, the two current dipole sources with four-shell concentric sphere model were reconstructed. Our experiments demonstrate that MSVR based on the support vector machine can obtain more robust estimations for EEG source localization problem.

关键词： EEG ISOMAP ERP IRWLS multidimensional support vector regression IRWLS

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The Method of multidimensional support vector regression for Moving Dipole Localization of Face Ezpression

The Method of Multidimensional Support Vector Regression for...

引用

The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

作者： Jian-wei LI You-hua WANG Qing WU Jin-long An Yu-fang WEI Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology TianJin China

Brain signal source localization is a process of inverse calculation from electroencephalogram (EEG) signal. A new method of multidimensional support vector regression (MSVR) with similar iterative re-weight least square (IRWLS) is firstly used in source localization of face expression. In order to discover the relationship between sensor information and internal source in the brain, the moving dipole with four-shell concentric sphere model was reconstructed. Its location parameters and components were fitted in a series of time points. EEG signals of face expression were adopted in our experiments. Satisfactory results demonstrate that MSVR based on the support vector machine can obtain more robust estimations for EEG inverse problem.

关键词： EEG inverse problem multidimensional support vector regression moving dipole face ezpression

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EEG SOURCE LOCALIZATION OF ERP BASED ON multidimensional support vector regression APPROACH

EEG SOURCE LOCALIZATION OF ERP BASED ON MULTIDIMENSIONAL SUP...

引用

2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： QING WU JIAN-WEI LI JIN-LONG AN YU-FANG WEI YOU-HUA WANG School of Computer Science and Software Hebei University of Technology Tianjin 300130 China School of Electrical Engineering and Automation Hebei University of Technology Tianjin 300130 Chi

关键词： EEG ISOMAP ERP IRWLS multidimensional support vector regression IRWLS

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Research on the Neural Dipole Localization Using a Method Combining SVM with Nonlinear Dimensionality Reduction

Research on the Neural Dipole Localization Using a Method Co...

引用

3rd International Conference on Bioinformatics and Biomedical Engineering

作者： Li, Jianwei Wang, Youhua Zong, Guilong Wu, Qing Hebei Univ Technol Prov Minist Joint Key Lab Electromagnet Field & E Tianjin 300130 Peoples R China

ISBN: (纸本)9781424429011

Electroencephalogram (EEG) source localization is well known as an import inverse problem of electrophysiology. In order to improve the accuracy of inverse calculation from EEG signal, a new method combining multidimensional SVR with Nonlinear dimensionality reduction was proposed. In our study, the ISOMAP algorithm was firstly used to find the low dimensional manifolds from high dimensional EEG signal. Then, a new method of multidimensional support vector regression (MSVR) with similar iterative re-weight least square (IRWLS) was applied to discover the parameters of EEG signals. In our experiments, EEG signals of epileptic spike were adopted as the objects. The satisfactory results were obtained.

关键词： EEG inverse problem multidimensional support vector regression ISOMAP IRWLS Epileptic spike

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support vector MACHINE METHOD USING IN EEG SIGNALS STUDY OF EPILEPTIC SPIKE

SUPPORT VECTOR MACHINE METHOD USING IN EEG SIGNALS STUDY OF ...

引用

International Conference on Machine Learning and Cybernetics

作者： Li, Jian-Wei Wang, You-Hua Zong, Gui-Long Wu, Qing Hebei Univ Technol Prov Minist Joint Key Lab Electromagnet Field & E Tianjin 300130 Peoples R China

ISBN: (纸本)9781424447053

support vector machine (SVM) is a new method of Machine Learning. SVR algorithms are normally only used for single-output systems now. Several SVR models were evaluated to identify one appropriate for multi-input multi-output systems, which require a much more complex control system. Based on good understanding of the SVM theory and algorithm, our studies discussed the multi-dimensional support vector regression (MSVR) and improved its algorithms. Electroencephalogram (EEG) source localization is well known as an import inverse problem of electrophysiology. In order to improve the accuracy of inverse calculation from EEG signal, MSVR is first applied in inverse problems, it has the advantages of simpler operation, faster convergence and better effect compared with single output SVR.

关键词： EEG inverse problem multidimensional support vector regression IRWLS Epileptic spike

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Research on the Neural Dipole Localization Using a Method Combining SVM with Nonlinear Dimensionality Reduction

Research on the Neural Dipole Localization Using a Method Co...

引用

The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

作者： Jianwei LI Youhua WANG Guilong ZONG Qing WU Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin 300130China