Publication: Comparison of discrete wavelet and Fourier transformsfor ECG beat classification
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Institution of Engineering and Technology (IET)
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Abstract
Two feature extraction methods, Fourier and wavelet analyses for ECG beat classification, are comparatively investigated. ECG features are searched by dynamic programming according to the divergence values. 10 types of ECG beat from an MTT-BIH database are classified with a success of 97% using a restricted Coulomb energy neural network trained by genetic algorithms.
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Electronics Letters
ISSN
0013-5194
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OPEN