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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Type-2 Fuzzy Sets Applied to Pattern Matching for the Classification of Cries of Infants under Neurological Risk
verfasst von : Karen Santiago-Sánchez, Carlos A. Reyes-García, Pilar Gómez-Gil
Erschienen in: Emerging Intelligent Computing Technology and Applications
Verlag: Springer Berlin Heidelberg
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Crying is an acoustic event that contains information about the functioning of the central nervous system, and the analysis of the infant´s crying can be a support in the distinguishing diagnosis in cases like asphyxia and hyperbilirrubinemia. The classification of baby cry has been intended by the use of different types of neural networks and other recognition approaches. In this work we present a pattern classification algorithm based on fuzzy logic Type 2 with which the classification of infant cry is realized. Experiments as well as results are also shown.