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- W1569362069 abstract "ECG pattern recognition using artificial neural networks is now an established paradigm. Diagnostic systems derive robustness, reliability and speed because of the automatic pattern classifiers. However, a common problem associated with these types of classifiers is to decide the optimal number of exemplars. This paper attempts to find an optimal number of exemplars required for training a multilayer perceptron with acceptable accuracy. Extensive experimentation suggests a figure of 200. Although this figure is specific for multilayer perceptron based classifier, experimentation on similar lines can be performed for other ANN topologies." @default.
- W1569362069 created "2016-06-24" @default.
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- W1569362069 date "2009-04-01" @default.
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- W1569362069 title "Deciding optimal number of exemplars for designing an ECG pattern classifier using MLP" @default.
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- W1569362069 doi "https://doi.org/10.17485/ijst/2009/v2i4/29429" @default.
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