An efficient code for environmental sound classification

AUTOR(ES)

Arora, Raman

FONTE

Acoustical Society of America

RESUMO

An efficient code for classifying environmental sounds is described that exploits a recent significant advance in signal processing known as compressed sensing (CS) [cf.Donoho, D. (2006). IEEE Trans. Inf. Theory 52, 1289–1306]. CS involves a novel approach to sampling in which the salient information in signals is recovered from the projection onto a small set of random basis functions. The advantage of the random basis over traditional Fourier or wavelet representations is that it allows accurate classification at low target-to-interference ratios based on few samples and little or no prior information about signals.

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