A statistical model for detecting jumps and decaying pulses in the presence of a background noise

C. M. Chan; Shiu Keung Tang; H. Wong

doi:10.1016/j.apacoust.2008.04.007

A statistical model for detecting jumps and decaying pulses in the presence of a background noise

C. M. Chan, Shiu Keung Tang, H. Wong

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

A statistical modeling technique using full Bayesian approach is proposed for use in the detection of jumps and decaying pulses in the presence of background noises. Two distributions, namely, the exponential-power and the Student-t distributions, are adopted for the purpose. Results suggest that both these distributions can give accurate recovery of the instants when the abrupt changes take place if the background noise level is lower than that of the changes by 3 dB. They also indicate that the exponential-power distribution is more useful when the signal-to-noise ratio falls below 0 dB.

Original language	English
Pages (from-to)	498-506
Number of pages	9
Journal	Applied Acoustics
Volume	70
Issue number	3
DOIs	https://doi.org/10.1016/j.apacoust.2008.04.007
Publication status	Published - 1 Mar 2009

Keywords

Gibbs sampling
Mixing parameter
Scale mixtures
Signals
Statistical distributions
Statistical modeling

ASJC Scopus subject areas

Acoustics and Ultrasonics

More information

10.1016/j.apacoust.2008.04.007

Cite this

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AB - A statistical modeling technique using full Bayesian approach is proposed for use in the detection of jumps and decaying pulses in the presence of background noises. Two distributions, namely, the exponential-power and the Student-t distributions, are adopted for the purpose. Results suggest that both these distributions can give accurate recovery of the instants when the abrupt changes take place if the background noise level is lower than that of the changes by 3 dB. They also indicate that the exponential-power distribution is more useful when the signal-to-noise ratio falls below 0 dB.

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KW - Scale mixtures

KW - Signals

KW - Statistical distributions

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ER -

A statistical model for detecting jumps and decaying pulses in the presence of a background noise

Abstract

Keywords

ASJC Scopus subject areas

More information

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