Similarity classification for bio-signals using fuzzy table look-up by distance and eigenvector

Author

Yoon, Y.R. ; Shin, J.W. ; Principe, Jose

Author_Institution

Dept. of Biomed. Eng., Yonsei Univ., Seoul, South Korea

Volume

1

fYear

2002

fDate

2002

Firstpage

34

Abstract

In this paper, two kinds of features, the distance and the angle difference of eigenvectors between two signals, were selected to input a fuzzy similarity inference system. Twelve visual evoked potential (VEP) signals were experimented on to test the fuzzy classification of similarity, and they were compared to each other in similarity. The similarity was taken by the regular section, so the the partial similarity analysis was available, and the total degree of similarity was calculated by averaging to similarity of each section.

Keywords

eigenvalues and eigenfunctions; feature extraction; fuzzy set theory; medical signal processing; visual evoked potentials; bio-signals; eigenvectors angle difference; fuzzy similarity inference system; fuzzy table look-up; partial similarity analysis; similarity averaging; similarity classification; visual evoked potential signals; Biomedical computing; Biomedical engineering; Euclidean distance; Fuzzy sets; Fuzzy systems; Input variables; Pattern matching; Signal analysis; Table lookup; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint

ISSN

1094-687X

Print_ISBN

0-7803-7612-9

Type

conf

DOI

10.1109/IEMBS.2002.1134374

Filename

1134374