[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5391/JKIIS.2004.14.1.082

Pattern Classification for Biomedical Signal using BP Algorithm and SVM

Kim, Man-Sun (한국표준과학연구원 인간정보그룹)
Lee, Sang-Yong (공주대학교 컴퓨터공학과)

Publication Information

Journal of the Korean Institute of Intelligent Systems / v.14, no.1, 2004 , pp. 82-87 More about this Journal

Abstract

ECG consists of various waveforms of electric signals of heat. Datamining can be used for analyzing and classifying the waveforms. Conventional studies classifying electrocardiogram have problems like extraction of distorted characteristics, overfitting, etc. This study classifies electrocardiograms by using BP algorithm and SVM to solve the problems. As results, this study finds that SVM provides an effective prohibition of overfitting in neural networks and guarantees a sole global solution, showing excellence in generalization performance.

Keywords

SVM; ECG; Datamining; BP algorithm; SVM; Neural Networks;

Citations & Related Records

Reference

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KSCI

Pattern Classification for Biomedical Signal using BP Algorithm and SVM BP알고리즘과 SVM을 이용한 심전도 신호의 패턴 분류

Pattern Classification for Biomedical Signal using BP Algorithm and SVM