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- Publisher Website: 10.1109/ICNIC.2005.1499852
- Scopus: eid_2-s2.0-33745236060
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Conference Paper: Design of a radial basis function neural network for attention tasks event related potentials extraction
Title | Design of a radial basis function neural network for attention tasks event related potentials extraction |
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Authors | |
Keywords | Event-Related Potential Partial Least Square Regression Radial Basis Function Neural Network |
Issue Date | 2005 |
Citation | 2005 First International Conference On Neural Interface And Control, Proceedings, 2005, p. 100-103 How to Cite? |
Abstract | Electroencephalogram (EEG) based biofeedback is widely employed to treat certain kinds of diseases especially Attention Deficit Hyperactivity Disorder (ADD/ADHD). Thus to design a system capable of learning a particular mapping between EEG features and different attention-level mental tasks is of great significance. Event Related Potentials (ERP) is such a powerful feature which is traditionally extracted by averaging. The paper proposed a new ERP extraction algorithm using radial basis function (RBF) neural network. It discussed the configuration, learning and running of the designed network. In order to reduce computational complexity and the influence of noise in estimating ERP, the partial least square regression was introduced to train the RBF network. Series experiments showed that the method is effective and is suitable for single-trail ERP estimation. © 2005 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/176247 |
References |
DC Field | Value | Language |
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dc.contributor.author | Liu, M | en_US |
dc.contributor.author | Wang, J | en_US |
dc.contributor.author | Yan, N | en_US |
dc.date.accessioned | 2012-11-26T09:07:55Z | - |
dc.date.available | 2012-11-26T09:07:55Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.citation | 2005 First International Conference On Neural Interface And Control, Proceedings, 2005, p. 100-103 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/176247 | - |
dc.description.abstract | Electroencephalogram (EEG) based biofeedback is widely employed to treat certain kinds of diseases especially Attention Deficit Hyperactivity Disorder (ADD/ADHD). Thus to design a system capable of learning a particular mapping between EEG features and different attention-level mental tasks is of great significance. Event Related Potentials (ERP) is such a powerful feature which is traditionally extracted by averaging. The paper proposed a new ERP extraction algorithm using radial basis function (RBF) neural network. It discussed the configuration, learning and running of the designed network. In order to reduce computational complexity and the influence of noise in estimating ERP, the partial least square regression was introduced to train the RBF network. Series experiments showed that the method is effective and is suitable for single-trail ERP estimation. © 2005 IEEE. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | 2005 First International Conference on Neural Interface and Control, Proceedings | en_US |
dc.subject | Event-Related Potential | en_US |
dc.subject | Partial Least Square Regression | en_US |
dc.subject | Radial Basis Function Neural Network | en_US |
dc.title | Design of a radial basis function neural network for attention tasks event related potentials extraction | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Yan, N: nyan@hku.hk | en_US |
dc.identifier.authority | Yan, N=rp00978 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1109/ICNIC.2005.1499852 | en_US |
dc.identifier.scopus | eid_2-s2.0-33745236060 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-33745236060&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.spage | 100 | en_US |
dc.identifier.epage | 103 | en_US |
dc.identifier.scopusauthorid | Liu, M=22835742800 | en_US |
dc.identifier.scopusauthorid | Wang, J=15066366300 | en_US |
dc.identifier.scopusauthorid | Yan, N=7102919410 | en_US |