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Genetic fuzzy relational neural network for infant cry classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2011) 6718 LNCS 288-296
DOI: 10.1007/978-3-642-21587-2_31
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Abstract

In this paper we describe a genetic fuzzy relational neural network (FRNN) designed for classification tasks. The genetic part of the proposed system determines the best configuration for the fuzzy relational neural network. Besides optimizing the parameters for the FRNN, the fuzzy membership functions are adjusted to fit the problem. The system is tested in several infant cry database reaching results up to 97.55%. The design and implementation process as well as some experiments along with their results are shown. © 2011 Springer-Verlag Berlin Heidelberg.

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Rosales-Pérez, A., Reyes-García, C. A., & Gómez-Gil, P. (2011). Genetic fuzzy relational neural network for infant cry classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6718 LNCS, pp. 288–296). https://doi.org/10.1007/978-3-642-21587-2_31

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