Abstract
Learning Vector Quantization (LVQ) is an algorithm widely used for solving classification problems. Some works include [1] where the algorithm was used for classifying faulty LEDs, in Fallah et al. (Proceedings of International MultiConference of Engineers and Computer Scientists, IMECS 2010. Hong Kong [2]) LVQ was used for iris recognition and classification using an artificial vision system. In addition in recent work LVQ has been also used for arrhythmia classification with a modular architecture (Melin et al. in Informatics and Computer Science Intelligent Systems Applications. Information Sciences 279:483–497, 2014 [3]).
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Amezcua, J., Melin, P., Castillo, O. (2018). Problem Statement. In: New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-73773-7_3
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DOI: https://doi.org/10.1007/978-3-319-73773-7_3
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