DocumentCode :
2319219
Title :
An Algorithm of General Closeness Degree Based on Evidence Theory and Its Applications in Fuzzy Pattern Recognition
Author :
Li, Ling-ling ; Li, Zhi-Gang ; Zhao, Quan-ming ; Zhang, Hui-juan
Author_Institution :
Dept. of Electr. Eng. & Autom., Hebei Univ. of Technol., Tianjin
fYear :
2006
fDate :
5-8 Dec. 2006
Firstpage :
1
Lastpage :
5
Abstract :
With the different features and applications for each of the conventional closeness degree algorithms, the mistake will be brought in pattern recognition if it was not selected correctly. Based on the combination rules in D-S evidence theory, a new algorithm was proposed by balance weighted between two conventional closeness degrees. The calculated data corresponding each conventional closeness degree was weighted as independent evidence; the weights were adjusted adaptively in terms of the distribution of pattern eigenvalue. The new algorithm combines the membership degree with closeness degree and can calculate the pattern eigenvalues represented by general real number, sections and fuzzy sets on the real number domain, which integrates the direct method and indirect method in pattern recognition. In every item of evidence there are weighted factors and the weights can be adjusted adaptively, so the recognition exactness rate can be improved. The validity of this algorithm was confirmed by two examples
Keywords :
fuzzy set theory; pattern recognition; DS evidence theory; fuzzy pattern recognition; fuzzy sets; general closeness degree; membership degree; pattern eigenvalues; Artificial neural networks; Automation; Character recognition; Clustering algorithms; Data processing; Eigenvalues and eigenfunctions; Fuzzy sets; Genetic algorithms; Pattern analysis; Pattern recognition; Fuzzy pattern recognition; balance weighted adaptively; evidence theory; general closeness degree; weighted combination of evidence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on
Conference_Location :
Singapore
Print_ISBN :
1-4244-0341-3
Electronic_ISBN :
1-4214-042-1
Type :
conf
DOI :
10.1109/ICARCV.2006.345376
Filename :
4150199
Link To Document :
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