Noise Classification Based on GMM and AANN

Abstract:

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In this paper, Gaussian Mixture model (GMM) as specific method is applied to noise classification. On this basis, a modified Gaussian Mixture Model with an embedded Auto-Associate Neural Network (AANN) is proposed. It integrates the merits of GMM and AANN. We train GMM and AANN as a whole and they are trained by means of Maximum Likelihood (ML). In the process of training, the parameter of GMM and AANN are updated alternately. AANN reshapes the distribution of the data and improves the similarity of the feature data in the same distribution type of noise. Experiments show that the GMM with embedded AANN improves accuracy rate of noise classification against baseline GMM.

Info:

Periodical:

Edited by:

Qi Luo

Pages:

1847-1853

DOI:

10.4028/www.scientific.net/AMM.58-60.1847

Citation:

Y. Zhang et al., "Noise Classification Based on GMM and AANN", Applied Mechanics and Materials, Vols. 58-60, pp. 1847-1853, 2011

Online since:

June 2011

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Price:

$35.00

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