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ICASSP
2009
IEEE

A nonparametric test for stationarity based on local Fourier analysis

10 years 4 months ago
A nonparametric test for stationarity based on local Fourier analysis
In this paper we propose a nonparametric hypothesis test for stationarity based on local Fourier analysis. We employ a test statistic that measures the variation of time-localized estimates of the power spectral density of an observed random process. For the case of a white Gaussian noise process, we characterize the asymptotic distribution of this statistic under the null hypothesis of stationarity, and use it to directly set test thresholds corresponding to constant false alarm rates. For other cases, we introduce a simple procedure to simulate from the null distribution of interest. After validating the procedure on synthetic examples, we demonstrate one potential use for the test as a method of obtaining a signal-adaptive means of local Fourier analysis and corresponding signal enhancement scheme.
Prabahan Basu, Daniel Rudoy, Patrick J. Wolfe
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Prabahan Basu, Daniel Rudoy, Patrick J. Wolfe
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