Intelligent systems and applications in engineering advanced technology and science

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dc.contributor.authorCeylan, Rahime
dc.date.accessioned2020-03-26T19:45:22Z
dc.date.available2020-03-26T19:45:22Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesi, Teknoloji Fakültesi, Elektirik ve Elektronik Mühendisliği Bölümüen_US
dc.description.abstractFeature extraction that is detection of effective features is one of the phases of biomedical signal classification. In feature extraction phase, the detection of features that increase performance of classification is very important in terms of diagnosis of disease. Due to this reason, the using of an effective algorithm for feature extraction increases classification accuracy and also it decreases processing time of classifier. In this study, two well-known dictionary-learning algorithms are used to extract features of ECG signals. The features of ECG signals are extracted by using Method of Optimal Direction (MOD) and K-Singular Value Decomposition (K-SVD). However, the extracted features are classified by Artificial Neural Network (ANN). Twelve different ECG signal classes which taken from MIT-BIH ECG Arrhythmia Database are used. When the obtained results are examined, it is seen that performance of classifier increases in usage of K-SVD for feature extraction. The highest classification accuracy is obtained as 98.74% with 5 nonzero elements in [20 1] feature vector, while K-SVD is used in feature extraction phase. The obtained results are assessed by comparing with the results obtained when discrete wavelet transform and principal component analysis are useden_US
dc.identifier.citationCeylan, R. (2018). Intelligent Systems and Applications in Engineering Advanced Technology and Science. International Journal of Intelligent Systems and Applications in Engineering, 6(1), 40-46.
dc.identifier.endpage46en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issue1en_US
dc.identifier.startpage40en_US
dc.identifier.urihttp://www.trdizin.gov.tr/publication/paper/detail/TWpZNE16TXpNdz09
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36029
dc.identifier.volume6en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorCeylan, Rahime
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.subjectECG Classification
dc.subjectMethod of Optimal Direction
dc.subjectValue Decomposition
dc.titleIntelligent systems and applications in engineering advanced technology and scienceen_US
dc.typeArticleen_US

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