Fuzzy non-reducible descriptors

Authors:
Ventzeslav Valev;Asai Asaithambi
Affiliations:
Department of Computer Science, Parks College of Engineering and Aviation, Saint Louis University, 3450 Lindell Boulevard, St. Louis, MO;Department of Computer Science, Parks College of Engineering and Aviation, Saint Louis University, 3450 Lindell Boulevard, St. Louis, MO
Venue:
Machine Graphics & Vision International Journal
Year:
2003

Citing 3
Cited 1

Fuzzy mathematical approach to pattern recognition

Fuzzy mathematical approach to pattern recognition
Fuzzy sets and fuzzy logic: theory and applications

Fuzzy sets and fuzzy logic: theory and applications
Construction of Boolean Decision Rules for ECG Recognition By Non- Reducible Descriptors

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2

Supervised pattern recognition with heterogeneous features

Machine Graphics & Vision International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a model for supervised pattern recognition problems in which the features of patterns are fuzzy numbers. Non-Reducible Descriptors (NRDs) for such problems are obtained through the use of a threshold value, which is calculated based on the distance between patterns defined in a manner similar to Hamming distance between binary sequences. Boolean formulas are used to represent these Fuzzy NRDs. This model is useful in a wide variety of applications, and we illustrate its usefulness with a medical application.