Titlebook: Artificial Neural Networks in Pattern Recognition; 4th IAPR TC3 Worksho Friedhelm Schwenker,Neamat Gayar Conference proceedings 2010 Spring

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Max Born,Peter Brix,Rolf Nevanlinnaabilities in order to carry out emotion classification within a Bayesian setup. Preliminary experiments in emotion recognition from speech signals from the WaSeP© dataset show that the proposed approach is effective, and it may outperform state-of-the-art classifiers.

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Sur le théorème de préparation de Weierstraßng results to the allowed fuzziness level and the size of data history used. This study has shown that different datasets behave differently with changing these factors. Dataset behavior is correlated with the separation between clusters of the dataset.

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