Comparison of Feature Reduction Methods in the Task of Arrhythmia Classification-Reference-Cited by-同舟云学术

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Comparison of Feature Reduction Methods in the Task of Arrhythmia Classification

Published:2014 Issue: Volume: Page:375-382
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Zaorálek Lukáš,Peterek Tomáš,Dohnálek Pavel,Gajdoš Petr

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-08156-4_37

Reference11 articles.

1. Lin, C.-H., Kuo, C.-L., Chen, J.-L., Chang, W.-D.: Fractal features for car-diac arrhythmias recognition using neural network based classifier. In: International Conference on Networking, Sensing and Control, ICNSC 2009, March 26-29, pp. 930–935 (2009), doi:10.1109/ICNSC.2009.4919405

2. Osowski, S., Siroic, R., Siwek, K.: Genetic algorithm for integration of ensemble of classifiers in arrhythmia recognition. In: Instrumentation and Measurement Technology Conference, I2MTC 2009, May 5-7, pp. 1496–1500. IEEE (2009), doi:10.1109/IMTC.2009.5168692

3. Lin, C.-H., Chen, P.-J., Chen, Y.-F., Lee, Y.-Y., Chen, T.: Multiple Cardiac Arrhythmia Recognition Using Adaptive Wavelet Network. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005, January 17-18, pp. 5655–5659 (2006), doi:10.1109/IEMBS.2005.1615769

4. Das, M.K., Ari, S.: ECG arrhythmia recognition using artificial neural network with S-transform based effective features. In: 2013 Annual IEEE India Conference (INDICON), December 13-15, pp. 1–6 (2013), doi:10.1109/INDCON.2013.6726153

5. Masters, T.: Practical Neural Network Recipes in C++. Academic Press, New York (1993)

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1. Graph Drawing Using Dimension Reduction Methods;Advances in Intelligent Systems and Computing;2015

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