Novel pattern recognition methods for arrhythmia classification / Aya Fawzy Sayed Ahmed ; Supervised Yasser M. Kadah , Mohamed I. Owis , Inas A. Yassine
Material type: TextLanguage: English Publication details: Cairo : Aya Fawzy Sayed Ahmed , 2015Description: 73 P. : charts ; 30cmOther title:- طرق متقدمه فى التعرف على الانماط لتشخيص لانظمية القلب [Added title page title]
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Item type | Current library | Home library | Call number | Copy number | Status | Date due | Barcode | |
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.03.M.Sc.2015.Ay.N (Browse shelf(Opens below)) | Not for loan | 01010110066472000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.03.M.Sc.2015.Ay.N (Browse shelf(Opens below)) | 66472.CD | Not for loan | 01020110066472000 |
Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering
We presented several approaches to enhance the performance of arrhythmia CAD system by introducing modifications on feature extraction and classification methods. In the first approach, spectral correlation coefficients were estimated for arrhythmias of interest. In the other three approaches, novel Bayesian and KNN ensembles employing the structures of one-versus-all and one-versus-one used for multi-class SVM classifier were introduced. The proposed methods outperformed all studies in comparison. In addition, the testing time follows AAMI standards
Issued also as CD
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