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