Transient acoustic signal classification using joint sparse representation

In this paper, we present a novel joint sparse representation based method for acoustic signal classification with multiple measurements. The proposed method exploits the correlations among the multiple measurements with the notion of joint sparsity for improving the classification accuracy. Extensive experiments are carried out on real acoustic data sets and the results are compared with the conventional discriminative classifiers in order to verify the effectiveness of the proposed method.

[1]  S. Srinivasan,et al.  Acoustic classification of battlefield transient events using wavelet sub-band features , 2007, SPIE Defense + Commercial Sensing.

[2]  Joel A. Tropp,et al.  ALGORITHMS FOR SIMULTANEOUS SPARSE APPROXIMATION , 2006 .

[3]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Volkan Cevher,et al.  Model-based compressive sensing for signal ensembles , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[5]  Alan S. Willsky,et al.  A Wavelet Packet Approach to Transient Signal Classification , 1995 .

[6]  Deanna Needell,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.

[7]  Shlomo Engelberg,et al.  Recovery of Edges from Spectral Data with Noise - A New Perspective , 2007, SIAM J. Numer. Anal..

[8]  Guillermo Sapiro,et al.  Sparse Representation for Computer Vision and Pattern Recognition , 2010, Proceedings of the IEEE.

[9]  Michael Elad,et al.  On the Role of Sparse and Redundant Representations in Image Processing , 2010, Proceedings of the IEEE.

[10]  Somkiat Sampan,et al.  Neural Fuzzy Techniques In Vehicle Acoustic Signal Classification , 1997 .

[11]  J. Tropp.  Algorithms for simultaneous sparse approximation. Part II: Convex relaxation , 2006, Signal Process..

[12]  Daniele Salvati,et al.  IMPROVEMENT OF ACOUSTIC LOCALIZATION USING A SHORT TIME SPECTRAL ATTENUATION WITH A NOVEL SUPPRESSION RULE TEMPLATES FOR DAFX04, NAPLES, ITALY , 2009 .