A Calculating Method of Similarity Degree for Fuzzy Pattern Recognition

Author

Zhao, Quanming ; Li, Lingling ; Li, Zhigang ; Gao, Zhaohui ; Wang, Jiannan

Author_Institution

Dept. of Electron. Inf., Tianjin Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3420

Lastpage

3424

Abstract

In order to avoid error recognition in fuzzy pattern recognition, a new algorithm of closeness degree was proposed to calculate the similarity on a certain characteristic between the typical pattern and the pattern to be recognized, then a function of similarity degree was established. This algorithm featured in combining the membership degree with closeness degree by distributing different weights and ability to process pattern eigenvalue represented by real number or fuzzy set, adaptive adjusting weights to each closeness degree in terms of pattern eigenvalue so as to implement correct pattern recognition. The validity of this algorithm was approved by two examples

Keywords

eigenvalues and eigenfunctions; fuzzy set theory; pattern recognition; fuzzy pattern recognition; fuzzy set; pattern eigenvalue; similarity degree calculation; Automation; Character recognition; Computer errors; Eigenvalues and eigenfunctions; Electromagnetic fields; Fuzzy sets; Intelligent control; Pattern recognition; closeness degree; fuzzy pattern recognition; membership degree; similarity degree function;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713003

Filename

1713003