Study on extension-based fuzzy pattern recognition

Author

Zhang Xiayu ; Yu Yongquan ; Chen Baixing ; Tan Xingxing ; Ye Zhipeng

Author_Institution

Fac. of Comput., Guangdong Univ. of Technol., Guangzhou, China

fYear

2007

fDate

25-28 Nov. 2007

Firstpage

234

Lastpage

238

Abstract

Pattern recognition, especially fuzzy pattern recognition, has been a study hotspot and important application of the artificial intelligence and machine learning. To solve the shortages of the existing fuzzy pattern recognition, this paper puts forward a new method, which is based on extension theory. It firstly takes advantage of the basal concepts, such as matter-element, dependent function in extension theory, to set up an extension-based fuzzy pattern recognition model, and then uses an emulational instance-the voice recognition to testify it. It is proved that this new method can not only conquer the shortages of the existing fuzzy pattern recognition methods, but also have more efficiency and applications.

Keywords

fuzzy set theory; learning (artificial intelligence); pattern recognition; artificial intelligence; dependent function; fuzzy pattern recognition; machine learning; matter-element; Artificial intelligence; Character recognition; Conferences; Machine learning; Mathematical model; Pattern recognition; Target recognition; Fuzzy pattern recognition; dependent function; extension; matter-element;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-1355-3

Type

conf

DOI

10.1109/ICIAS.2007.4658381

Filename

4658381