Paper Title:
Wavelet Packet Analysis Based Feature Extraction of Vehicular Acoustic Signal
  Abstract

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, J. W. Ji, X. W. Han, Z. H. Yuan, "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
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