UM
A three-domain fuzzy support vector regression for image denoising and experimental studies
Liu Z.1; Xu S.2; Chen C.L.P.4; Zhang Y.1; Chen X.1; Wang Y.3
2014
Source PublicationIEEE Transactions on Cybernetics
ISSN21682267
Volume44Issue:4Pages:516-525
AbstractA novel three-domain fuzzy support vector regression (3DFSVR) is proposed, where the three-domain fuzzy kernel function (3DFKF) provides a solution to process uncertainties and input-output data information simultaneously. When compared with traditional two-domain SVR (2DSVR), the major advantage of 3DFSVR is able to use the prior knowledge via the novel fuzzy domain to analyze uncertain data and signals, which will enhance the potentials of 2DSVR. The 3DFKF is presented to integrate the kernel and fuzzy membership functions into a three-domain function. Definition and solution of the fuzzy convex optimization problem are presented to construct the whole theoretical framework. Experiments and simulation results show the effectiveness of 3DFSVR for the uncertain image denoising. © 2013 IEEE.
KeywordFuzzy support vector regression (FSVR) three-domain fuzzy kernel function (3DFKF) three-domain fuzzy support vector regression (3DFSVR) uncertain data
DOI10.1109/TSMCC.2013.2258337
URLView the original
Language英語
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Cited Times [WOS]:30   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Guangdong University of Technology
2.Dongguan Polytechnic
3.Hunan University
4.Universidade de Macau
Recommended Citation
GB/T 7714
Liu Z.,Xu S.,Chen C.L.P.,et al. A three-domain fuzzy support vector regression for image denoising and experimental studies[J]. IEEE Transactions on Cybernetics,2014,44(4):516-525.
APA Liu Z.,Xu S.,Chen C.L.P.,Zhang Y.,Chen X.,&Wang Y..(2014).A three-domain fuzzy support vector regression for image denoising and experimental studies.IEEE Transactions on Cybernetics,44(4),516-525.
MLA Liu Z.,et al."A three-domain fuzzy support vector regression for image denoising and experimental studies".IEEE Transactions on Cybernetics 44.4(2014):516-525.
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