Title :
An interval type-2 fuzzy perceptron
Author :
Rhee, Frank Chung-Hoon ; Hwang, Cheul
Author_Institution :
Dept. of Electron. Eng., Hanyang Univ., Ansan, South Korea
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper presents an interval type-2 fuzzy perceptron algorithm that is an extension of the type-1 fuzzy perceptron algorithm proposed by J. Keller et al. (1985). In our proposed method, the membership values for each pattern vector are extended as interval type-2 fuzzy memberships by assigning uncertainty to the type-1 memberships. By doing so, the decision boundary obtained by interval type-2 fuzzy memberships can converge to a more desirable location than the boundary obtained by crisp and type-1 fuzzy perceptron methods. Experimental results are given to show the effectiveness of our method
Keywords :
convergence; fuzzy neural nets; perceptrons; uncertainty handling; convergence; decision boundary; fuzzy membership functions; interval type-2 fuzzy perceptron algorithm; pattern vector membership values; type-1 memberships; uncertainty assignment; Computer vision; Convergence; Fuzzy systems; Iterative algorithms; Laboratories; Machine vision; Uncertainty; Vectors;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1006697
