Fuzzy Divergences Based on Tsallis Relative Entropy

被引：0
|
作者：
Rong, Lan [1 ]
Jiu-lun, Fan [1 ]
机构：
[1] Xian Inst Post & Telecommun, Sch Commun & Informat Engn, Xian 710121, Peoples R China
来源：
QUANTITATIVE LOGIC AND SOFT COMPUTING 2010, VOL 2 | 2010年 / 82卷
关键词：
Fuzzy divergence; Tsallis relative entropy; Distance measure; Fuzzy entropy; DISTANCE MEASURE;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy divergence describes the difference between two fuzzy sets. Based on Tsallis relative entropy, two classes of fuzzy divergence are proposed in this paper. Using the point of view off-divergence proposed by Csiszar, the properties of the two classes of fuzzy divergence are discussed. The notable feature of the two classes of fuzzy divergence is that they are both a-distance measures, thus new fuzzy entropy formulas can be induced by these fuzzy divergences.
引用
收藏
页码：359 / 368
页数：10
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