Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals

Objective: An autoencoder-based framework that simultaneously reconstruct and classify biomedical signals is proposed. Previous work has treated reconstruction and classification as separate problems. This is the first study that proposes a combined framework to address the issue in a holistic fashi...

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Vydáno v:	IEEE transactions on biomedical engineering Ročník 64; číslo 9; s. 2196 - 2205
Hlavní autoři:	Gogna, Anupriya, Majumdar, Angshul, Ward, Rabab
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.09.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Arrhythmia Body area network (BAN) Classification Compressed sensing Correlation Data processing deep learning EEG EKG Electrocardiography - methods Electroencephalography Image reconstruction Information Storage and Retrieval - methods Monitoring Pattern Recognition, Automated - methods Real time operation Reconstruction Signal analysis Signal classification Signal Processing, Computer-Assisted Supervised Machine Learning
ISSN:	0018-9294, 1558-2531
On-line přístup:	Získat plný text
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