Fuzzy Entropy: Axiomatic Definition and Neural Networks Model

被引：0

作者：

QING Ming CAO Yue HUANG TianminDepartment of Mathematics Southwest Jiaotong University Chengdu China ^{[610031
]}

Zhengzhou Teachers College Zhengzhou China ^{[450044
]}

机构：

来源：

数学季刊 | 2004年 / 03期

关键词：

neural networks; BP networks; fuzzy entropy; fuzzy set; model;

D O I：

暂无

中图分类号：

O157.5 [图论];

学科分类号：

070104 ;

摘要：

<正> The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.

引用

页码：319 / 323

页数：5

共 6 条

[1]

Measuring fuzzy uncertainty. NIKHIL R Pal,JAMES C Bezdek. IEEE Transactions on Fuzzy Systems .

[2]

Fuzzy entropy and conditioning. KOSKO B. Journal of Information Science . 1986

[3]

Probability measures of fuzzy events. ZADEH L A. J M A A . 1968

[4]

On measures of fuzziness and fuzzy complements. YAGER R R. International Journal of General Systems . 1979

[5]

A definition of nonprobabilistic entropy in the setting of fuzzy set theory. DE LUCA A,TERMINI S. Information and Control . 1972

[6]

Modeling a kind of fuzzy systems using fuzzy entropy. QING Ming,XU Yang,HUANG Tian-min. in Proc. International Conferences on Info-tech and Info-net . 2001

← 1 →