ENSEMBLE OF NEURAL NETWORKS FOR IMPROVED RECOGNITION AND CLASSIFICATION OF ARRHYTHMIA |
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| S. Osowski, T. Markiewicz, L. Tran Hoai |
- Abstract:
- The paper presents different methods of combining many neural classifiers into one ensemble system for recognition and classification of arrhythmia. Majority and weighted voting, Kullback-Leibler divergence and modified Bayes methods will be presented and compared. The numerical experiments will be performed for the problems concerning the recognition of different types of arrhythmia on the basis of ECG waveforms of MIT BIH AD.
- Keywords:
- neural classifiers, ensemble of classifiers, methods of integrations, arrhythmia recognition
- Download:
- PWC-2006-TC13-005u.pdf
- DOI:
- -
- Event details
- Event name:
- XVIII IMEKO World Congress
- Title:
Metrology for a Sustainable Development
- Place:
- Rio de Janeiro, BRAZIL
- Time:
- 17 September 2006 - 22 September 2006