Optimization of the LVQ Network Architectures with a Modular Approach for Arrhythmia Classification
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-26211-6_23
Reference30 articles.
1. Amezcua J., Melin P.: A modular LVQ neural network with fuzzy response integration for arrhythmia classification. In: IEEE 2014 Conference on Norbert Wiener in the 21st century, Boston, June 2014
2. Amezcua J., Melin P.: Optimization of Modular Neural Networks with the LVQ Algorithm for Classification of Arrhythmias using Particle Swarm Optimization, Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence Book 547, pp. 307–314. Springer, 2014
3. Anuradha B., Veera-Reddy V.C.: Cardiac arrhythmia classification using fuzzy classifiers. J. Theor. Appl. Inform. Technol. 353–359 (2005)
4. Biswal, B., Biswal, M., Hasan, S., Dash, P.K.: Nonstationary power signal time series data classification using LVQ classifier. Appl. Soft Comput. Elsevier 18, 158–166 (2014)
5. Castillo, O., Melin, P., Ramirez, E., Soria, J.: Hybrid intelligent system for cardiac arrhythmia classification with Fuzzy K-Nearest Neighbors and neural networks combined with a fuzzy system. J. Expert Syst. Appl. 39(3), 2947–2955 (2012)
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