PCA Representation of ECG Signal as a Useful Tool for Detection of Premature Ventricular Beats in 3-Channel Holter Recording by Neural Network and Support Vector Machine Classifier

Author:

Jankowski Stanisław,Dusza Jacek J.,Wierzbowski Mariusz,Oręziak Artur

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Bausá Lamazares, D.: Morphological Classification of ECG Holter Recording by Principal Component Analysis (PCA) and Support Vector Machine (SVM), Final Project (SOCRATES/ERASMUS), Warsaw Institute of Technology (2003)

2. Bishop, C.M.: Neural networks for pattern recognition. Clarendon Press, Oxford

3. Cover, T.M.: Geometrical and Statistical Properties of Systems of Linear Inequalities with Application in Pattern Recognition. IEEE Transaction on Electronic Computers, 326–334 (June 1965)

4. Dubois, R.: Application des nouvelles méthodes d’apprentissage à la détectionprécoce d’anomalies en électrocardiographie, Ph.D. thesis, Université Paris 6 (2003)

5. Lecture Notes in Computer Science;S. Jankowski,2002

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