Studies on Fuzzy Information Measures

Abstract

Fuzzy information measure is a measure between two pattern vectors in fuzzy circumstance. In this paper, an axiom theory about fuzzy entropy is surveyed, and all kinds of definitions of fuzzy entropy are discussed firstly. And then based on the idea of Shannon information entropy, two concepts of fuzzy joint entropy and fuzzy conditional entropy are proposed and the basic properties of them are given and proved. At last, the classical similarity measures, such as dissimilarity measure (DM) and similarity measure (SM) are studied, and then two new measures, fuzzy absolute information measure (FAIM) and fuzzy relative information measure (FRIM) are set up, which can be a measure between a fuzzy set A and B. So, it provides a new research approach for studies on pattern similarity measure