DocumentCode :
60496
Title :
A Three-Domain Fuzzy Support Vector Regression for Image Denoising and Experimental Studies
Author :
Zhi Liu ; Shuqiong Xu ; Chen, C.L.P. ; Yun Zhang ; Xin Chen ; Yaonan Wang
Author_Institution :
Fac. of Autom., Guangdong Univ. of Technol., Guangzhou, China
Volume :
44
Issue :
4
fYear :
2014
fDate :
Apr-14
Firstpage :
516
Lastpage :
525
Abstract :
A 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.
Keywords :
convex programming; fuzzy set theory; humanoid robots; image denoising; regression analysis; 2DSVR; 3DFKF; 3DFSVR; fuzzy convex optimization; image denoising; three-domain fuzzy kernel function; three-domain fuzzy support vector regression; two-domain SVR; Fuzzy support vector regression (FSVR); three-domain fuzzy kernel function (3DFKF); three-domain fuzzy support vector regression (3DFSVR); uncertain data;
fLanguage :
English
Journal_Title :
Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2267
Type :
jour
DOI :
10.1109/TSMCC.2013.2258337
Filename :
6516014
Link To Document :
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