Embedded Classification Kernel Using Som Clustering and Mixture of Experts

Abstract

-In this paper, we introduce a new classification kernel by embedding self organized map (SOM) clustering with mixture of radial basis function (RBF) networks. The model’s efficacy is demonstrated in solving a multi-class TIMIT speech recognition problem where the kernel is used to learn the multidimensional cepstral feature vectors to estimate their… (More)

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Cite this paper

@inproceedings{Meenakshisundaram2005EmbeddedCK, title={Embedded Classification Kernel Using Som Clustering and Mixture of Experts}, author={Sankaranarayanan Meenakshisundaram and S. S. Dlay and W. L. Woo}, year={2005} }