Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/88462
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dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorJiang, Yen_US
dc.creatorLeung, HFen_US
dc.date.accessioned2020-11-26T03:24:42Z-
dc.date.available2020-11-26T03:24:42Z-
dc.identifier.isbn978-1-5386-6811-5 (Electronic)en_US
dc.identifier.isbn978-1-5386-6810-8 (USB)en_US
dc.identifier.isbn978-1-5386-6812-2 (Print on Demand(PoD))en_US
dc.identifier.urihttp://hdl.handle.net/10397/88462-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Y. Jiang and F. H. F. Leung, "Fisher Discriminant Analysis with New Between-class Scatter Matrix for Audio Signal Classification," 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), Shanghai, China, 2018, pp. 1-5 is available at https://dx.doi.org/10.1109/ICDSP.2018.8631801en_US
dc.subjectFisher discriminant analysisen_US
dc.subjectModified Fisher discriminant analysisen_US
dc.subjectNew between-class scatter matrixen_US
dc.subjectAudio signal classificationen_US
dc.titleFisher discriminant analysis with new between-class scatter matrix for audio signal classificationen_US
dc.typeConference Paperen_US
dc.identifier.spage1en_US
dc.identifier.epage5en_US
dc.identifier.doi10.1109/ICDSP.2018.8631801en_US
dcterms.abstractFisher Discriminant Analysis (FDA) is a widely used technique for signal classification. Its application varies from face recognition to speaker recognition. FDA aims to project a given feature onto a projected space, where the features coming from the same class are moved closer, while those coming from different classes are moved farther. However, in the original formulation of FDA, the number of orthogonal projection directions is limited by the number of classes, which may hinder the effectiveness of FDA as a projection technique. In this paper, we propose to use new between-class scatter matrices to replace the original between-class scatter matrix, in order to increase the number of orthogonal projection directions. We call FDA with these new between-class scatter matrices the Modified FDA (MFDA). The effectiveness of MFDA and FDA as a projection technique is compared through doing two audio signal classification tasks. Both linear version and kernel version of MFDA and FDA are evaluated, and experimental results show that MFDA can outperform FDA in both classification tasks.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), Shanghai, China, China, 19-21 Nov. 2018, p. 1-5en_US
dcterms.issued2018-11-
dc.relation.conferenceIEEE International Conference on Digital Signal Processing [DSP]en_US
dc.description.validate202011 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0512-n05en_US
dc.description.pubStatusPublisheden_US
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