A novel multichannel sparse convolutional autoencoder for electrocardiogram signal compression

Electrocardiogram (ECG) signal compression is paramount in continuously monitoring cardiac patients, as it reduces data storage and transmission costs. Deep neural networks, particularly autoencoders, offer significant potential for compressing ECG signals by mapping them to lower-dimensional spaces...

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Vydané v:	Journal of electrocardiology Ročník 93; s. 154125
Hlavní autori:	Bekiryazıcı, Tahir, Damkacı, Mehmet, Aydemir, Gürkan, Gürkan, Hakan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 01.11.2025
Predmet:	Cardiovascular Convolutional autoencoders ECG ECG compression Sparse autoencoders ECG ECG compression Sparse autoencoders Convolutional autoencoders
ISSN:	0022-0736, 1532-8430, 1532-8430
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