Blind Source Separation for the Aggregation of Machine Learning Algorithms: An Arrhythmia Classification Case

Blind Source Separation for the Aggregation of Machine Learning Algorithms: An Arrhythmia Classification Case

In this work, we present an application of the blind source separation (BSS) algorithm to reduce false arrhythmia alarms and to improve the classification accuracy of artificial neural networks (ANNs). The research was focused on a new approach for model aggregation to deal with arrhythmia types tha...

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Bibliographic Details
Main Authors: Krzysztof Gajowniczek, Iga Grzegorczyk, Michał Gostkowski, Tomasz Ząbkowski
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Electronics
Subjects:
arrhythmia
false alarm
blind source separation
machine learning
Online Access:https://www.mdpi.com/2079-9292/9/3/425

Internet

https://www.mdpi.com/2079-9292/9/3/425

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