Robust algorithm for arrhythmia classification in ECG using extreme learning machine
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1475-925X
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Robust algorithm for arrhythmia classification in ECG using extreme learning machine ; volume:8 ; number:1 ; day:28 ; month:10 ; year:2009 ; pages:1-12 ; date:12.2009
Biomedical engineering online ; 8, Heft 1 (28.10.2009), 1-12, 12.2009
- Creator
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Kim, Jinkwon
Shin, Hang Sik
Shin, Kwangsoo
Lee, Myoungho
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/1475-925X-8-31
- URN
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urn:nbn:de:101:1-2021081222251337981496
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:54 AM CEST
Data provider
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Associated
- Kim, Jinkwon
- Shin, Hang Sik
- Shin, Kwangsoo
- Lee, Myoungho
- SpringerLink (Online service)
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Impact of cardiac arrhythmia on velocity quantification by ECG gated phase contrast MRI
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Constrained transformer network for ECG signal processing and arrhythmia classification
Two-dimensional ECG-based cardiac arrhythmia classification using DSE-ResNet
Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Impact of cardiac arrhythmia on velocity quantification by ECG gated phase contrast MRI
Detection of Arrhythmia Heartbeats from ECG Signal Using Wavelet Transform-Based CNN Model
Arrhythmia Analysis in a Non-contact cECG Chair using Convolutional Neural Network
Retraction Note: Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals
Arrhythmia
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Deep learning-assisted arrhythmia classification using 2-D ECG spectrograms
Constrained transformer network for ECG signal processing and arrhythmia classification
Two-dimensional ECG-based cardiac arrhythmia classification using DSE-ResNet
Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Impact of cardiac arrhythmia on velocity quantification by ECG gated phase contrast MRI
Detection of Arrhythmia Heartbeats from ECG Signal Using Wavelet Transform-Based CNN Model
Arrhythmia Analysis in a Non-contact cECG Chair using Convolutional Neural Network
Retraction Note: Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals
Arrhythmia
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