Studies on Fuzzy Information Measures
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 fuzzt 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.
Fuzzy entropy similarity measure fuzzy absolute information measurement (FAMI) fuzzy relative information measurement (FRIM).
Shifei Ding Zhongzhi Shi Fengxiang Jin
College of Information Science and Engineering, Shandong Agricultural University, Taian 271018 P.R.C Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Aca College of Geo-Information Science and Engineering, Shandong University of Science and Technology, Q
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
292-296
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）