Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/231
Title: The effect of dictionary learning on weight update of AdaBoost and ECG classification
Authors: Barstuğan, Mücahid
Ceylan, Rahime
Keywords: Adaboost
Dictionary Learning
Ecg
Feature Subsets
Signal Classification
Sparse Representation
Features
Model
Issue Date: 2020
Publisher: ELSEVIER
Abstract: A signal can be represented by sparse representation with fewer coefficients. Due to this ability, sparse representation is used in research fields such as signal compression, noise elimination, and classification. In this study, sparse coefficients of the signals were obtained by using dictionary learning and sparse representation algorithms. The obtained coefficients were used in the weight update process of three different classifiers, which were created by using AdaBoost, SVM, and LDA algorithms. So, Dictionary learning based AdaBoost classifiers were obtained. The proposed Dictionary Learning (DL) based AdaBoost classifiers classified the ECG (Electrocardiography) signals. Before classification, the feature selection process was applied to ECG signals and six different feature subsets were obtained by Discrete Wavelet Transform (DWT), First Order Statistics (FOS), T-test, Bhattacharyya, Entropy, and Wilcoxon test methods. The feature subsets were used as the new dataset. The classification process was done by the proposed method and satisfying results were obtained. The best classification accuracy was obtained as 99.75% by the proposed dictionary learning based method called as DL-AdaBoost-SVM on feature subsets obtained by DWT and Wilcoxon test methods. (C) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.
URI: https://doi.org/10.1016/j.jksuci.2018.11.007
https://hdl.handle.net/20.500.13091/231
ISSN: 1319-1578
2213-1248
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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