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

机译:基于LVQ算法的新的神经网络模型用于心律失常的多类别分类

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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.
机译:本文介绍了竞争性神经网络与LVQ算法在心电图信号(ECG)分类中的应用。在本研究中,我们使用了MIT-BIH心律失常数据库,共15个类别。开发了三种采用模块化方法进行分类的体系结构。与使用相同数据库开发的用于心律失常分类的其他方法相比,由于使用了整个数据库,因此该方法产生了很好的结果。给出了仿真结果,并进行了统计测试,以比较分类结果非常相似的三种架构。

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