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Arrhythmia Detection by using Generative Adversarial Network Method: Analysis and Interpretation of Arrhythmia - Softcover

Sanamdikar, Sanjay; Hamde, Satish; Asutkar, Vinayak

 
9786206739135: Arrhythmia Detection by using Generative Adversarial Network Method: Analysis and Interpretation of Arrhythmia
Softcover
ISBN 10: 6206739139 ISBN 13: 9786206739135
Verlag: LAP LAMBERT Academic Publishing, 2023

Inhaltsangabe

This book explains how a deep generative adversarial network built on a large dataset may detect arrhythmias more accurately than physicians. Furthermore, feature extraction has traditionally been seen as an essential component of electrocardiogram arrhythmia classification The purpose of this research is to examine ECG arrhythmia classification using a deep dense generative adversarial network. The GAN architecture shown in this book can be taught to produce ECG signals that are comparable to real-world ECG signals. The results indicate that using a sequence-based strategy for all ECG-beat types substantially improves area under curve on our test set. Traditional architecture does not naturally address this structure, and therefore suffers from decreased performance when such a structure is informative. This book compares the proposed technique to kernel principle component analysis with incremental support vector regression, discrete wavelet transforms with incremental support vector regression and general sparse neural network. From obtained results, it is concluded that the proposed GAN technique is superior to these three methods with an overall accuracy of 97.44 percent.

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Über die Autorin bzw. den Autor

O Dr. Sanjay trabalha atualmente como Professor Associado no PDEAs College of Engineering Manjari Pune, Maharashtra, Índia. Tem um total de 21 anos de experiência no meio académico e na investigação. O seu livro publicado, Tratamento de esgotos usando PLC e Análise de Arritmia e Interpretação de Sinais ECG em publicações Lambert Academic.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
6206739139
ISBN 13 
9786206739135
Einband
Taschenbuch
Anzahl der Seiten
164
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
KreGa Onlinehandel GmbH
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info@krega-onlinehandel.de

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