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Fuzzy Entropy Construction for Non-Convex Fuzzy Membership Function
Sang H. Lee(이상혁),Jae Hyung Kim(김재형),Sangjin Kim(기상진) 한국지능시스템학회 2008 한국지능시스템학회 학술발표 논문집 Vol.18 No.1
Fuzzy entropy is designed for non-convex fuzzy membership function using well known Hamming distance measure. Design procedure of convex fuzzy membership function is represented through distance measure, furthermore characteristic analysis for non-convex function are also illustrated. Proof of proposed fuzzy entropy is discussed, and entropy computation is illustrated.
Similarity Measure Construction for Non-Convex Fuzzy Membership Function
Park Hyun Jeong(박현정),Sungshin Kim(김성신),Sang H. Lee(이상혁) 한국지능시스템학회 2008 한국지능시스템학회논문지 Vol.18 No.1
The similarity measure is constructed for non-convex fuzzy membership function using well known Hamming distance measure. Comparison with convex fuzzy membership function is carried out, furthermore characteristic analysis for non-convex function are also illustrated. Proposed similarity measure is proved and the usefulness is verified through example. In example, usefulness of proposed similarity is pointed out.
Fuzzy Entropy Construction based on Similarity Measure
Park Hyun Jeong(박현정),Insuk Yang(양인석),Soorok Ryu(류수록),Sang H. Lee(이상혁) 한국지능시스템학회 2008 한국지능시스템학회논문지 Vol.18 No.2
In this paper we derived fuzzy entropy that is based on similarity measure. Similarity measure represents the degree of similarity between two informations, those informations characteristics are not important. First we construct similarity measure between two informations, and derived entropy functions with obtained similarity measure. Obtained entropy is verified with proof. With the help of one-to-one similarity is also obtained through distance measure, this similarity measure is also proved in our paper.