A new neural network model based on the LVQ algorithm for multi-class classification of arrhythmias

被引：81

作者：

Melin, Patricia ^{[1
]}

Amezcua, Jonathan ^{[1
]}

Valdez, Fevrier ^{[1
]}

Castillo, Oscar ^{[1
]}

机构：

[1] Tijuana Inst Technol, Calzada Tecnologico 22379, Tijuana, Mexico

来源：

INFORMATION SCIENCES | 2014年 / 279卷

关键词：

LVQ; Clustering; Neural network; Classification; Arrhythmias; LEARNING VECTOR QUANTIZATION; RECOGNITION; SYSTEM;

D O I：

10.1016/j.ins.2014.04.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes the application of competitive neural networks with the LVQ algorithm for classification of electrocardiogram signals (ECG). For this study we used the MIT-BIH arrhythmia database with 15 classes. Three architectures were developed with a modular approach for classification. Compared with other methods that have been developed for classification of arrhythmias with this same database, the proposed approach produces very good results, because the entire database was used. Simulation results are presented, and a statistical test was performed to compare the three architectures which were very similar in the classification results. (C) 2014 Elsevier Inc. All rights reserved.

引用

页码：483 / 497

页数：15

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