Spectral Density Estimation for a Class of Spectrally Correlated Processes

JOURNAL OF TIME SERIES ANALYSIS(2024)

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摘要
We study the estimation problem of the spectral density function for harmonizable non-stationary processes. More precisely, we consider spectrally correlated processes whose spectral measure has the support contained in the union of unknown lines with possibly non-unit slopes. We propose the frequency-smoothed periodogram along the estimated support line as an estimator of the spectral density function. We show the mean-square consistency of the proposed estimator. Additionally, we discuss the estimation of the support line in a specific model with its applications in locating a moving source. Finally, we present simulations confirming the proven results.
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关键词
Frequency-smoothed periodogram,harmonizable process,non-stationarity,source locating problem,spectral analysis
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