A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique

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dc.contributor.author Khushaba, Rami en_US
dc.contributor.author Al-Ani, Ahmed en_US
dc.contributor.author Nguyen, Hung en_US
dc.contributor.author Al-Jumaily, Adel Ali en_US
dc.contributor.editor Wobcke, Wayne; Zhang, Mengjie en_US
dc.date.accessioned 2010-05-28T09:40:40Z
dc.date.available 2010-05-28T09:40:40Z
dc.date.issued 2008 en_US
dc.identifier 2008003244 en_US
dc.identifier.citation Khushaba Rami N et al. 2008, 'A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique', in http://dx.doi.org/10.1007/978-3-540-89378-3_55 (ed.), Springer, Germany, pp. 544-550. en_US
dc.identifier.issn 978-3-540-89377-6 en_US
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/8108
dc.description.abstract Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the Uncorrelated Linear Discriminant Analysis (ULDA). Although dimensionality reduction via ULDA can present a set of statistically uncorrelated features, but similar to the existing DA?s it assumes that the original data set is linearly separable, which is not the case with most real world problems. In order to overcome this problem, a one layer feed-forward ANN trained with a Differential Evolution (DE) optimization technique is combined with ULDA to implement a nonlinear feature projection technique. This combination acts as nonlinear discriminant analysis. The proposed approach is validated on a Brain Computer Interface (BCI) problem and compared with other techniques. en_US
dc.language en_US
dc.publisher Springer en_US
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/978-3-540-89378-3_55 en_US
dc.title A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique en_US
dc.parent Lecture Notes In Computer Science Vol 5360: AI 2008 Advances in Artificial Intelligence en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Germany en_US
dc.identifier.startpage 544 en_US
dc.identifier.endpage 550 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 170205 en_US
dc.personcode 101188 en_US
dc.personcode 040052 en_US
dc.personcode 011083 en_US
dc.personcode 840115 en_US
dc.percentage 100 en_US
dc.classification.name Neurocognitive Patterns and Neural Networks en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Feature projection - Nonlinear Discriminant Analysis en_US
dc.staffid en_US
dc.staffid 840115 en_US


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