Wavelet Packet Analysis Based Feature Extraction of Vehicular Acoustic Signal

Abstract:

Article Preview

In this paper, an approach based on wavelet packet analysis is proposed to deal with the problem that acoustic signal of moving vehicle is easily influenced by environmental noise in vehicle type classification. Wavelet packet analysis is applied to extract local and detail feature information of acoustic signal in the time-frequency domain. Firstly, raw acoustic signal is decomposed into different frequency bands by wavelet packet analysis, and then decomposition coefficients are reconstructed. The energy of every frequency band component is used to form the feature vector. Finally, vehicle type classification is implemented by RBF neural network on the basis of these feature vectors. Experimental results show that the proposed method is feasible and effective.

Info:

Periodical:

Edited by:

Qi Luo

Pages:

1593-1598

DOI:

10.4028/www.scientific.net/AMM.55-57.1593

Citation:

X. X. Qi et al., "Wavelet Packet Analysis Based Feature Extraction of Vehicular Acoustic Signal", Applied Mechanics and Materials, Vols. 55-57, pp. 1593-1598, 2011

Online since:

May 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.