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Introducing the hybrid “K-means, RLS” learning for the RBF network in obstructive apnea disease detection using Dual-tree complex wavelet transform based features Cover

Introducing the hybrid “K-means, RLS” learning for the RBF network in obstructive apnea disease detection using Dual-tree complex wavelet transform based features

Journal of Electrical Bioimpedance
Volume 11 (2020): Issue 1 (January 2020)
By: Javad Ostadieh and  Mehdi Chehel Amirani  
Open Access
|Mar 2020

Authors

Javad Ostadieh

j.ostadieh@urmia.ac.ir

Faculty of Electrical and Computer Engineering, Urmia University, Urmia

Mehdi Chehel Amirani

Faculty of Electrical and Computer Engineering, Urmia University, Urmia
DOI: https://doi.org/10.2478/joeb-2020-0002 | Journal eISSN: 1891-5469
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Language: English
Page range: 4 - 11
Submitted on: Dec 27, 2019
|
Published on: Mar 18, 2020
Published by: University of Oslo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Electrocardiogram,
Sleep Apnea,
RBF network,
Wavelet,
DT-CWT,
Feature extraction
Related subjects:
Engineering,
Bioengineering and biomedical engineering,
Biomedical electronics,
Life sciences,
Biophysics,
Medicine,
Biomedical engineering,
Physics,
Spectroscopy and metrology

© 2020 Javad Ostadieh, Mehdi Chehel Amirani, published by University of Oslo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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