Spectral density estimation

Known as: Spectrum estimation, Frequency estimation, Periodogram analysis 
In statistical signal processing, the goal of spectral density estimation (SDE) is to estimate the spectral density (also known as the power spectral… (More)
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Papers overview

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Highly Cited
2017
Highly Cited
2017
Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domain… (More)
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2015
2015
We develop a Bayesian modelling approach for spectral densities, built from a local Gaussian mixture approximation to the Whittle… (More)
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Highly Cited
2011
Highly Cited
2011
In this paper, we consider power spectral density estimation of bandlimited, wide-sense stationary signals from sub-Nyquist… (More)
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2011
2011
Traditional kernel spectral density estimators are linear as a function of the sample autocovariance sequence. The purpose of the… (More)
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2011
2011
The power spectral density of a signal can be estimated most accurately by using a window with a narrow bandwidth and large… (More)
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2009
2009
Self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. In this paper… (More)
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2007
2007
This correspondence introduces the use of sharpened periodograms for spectral density estimation. It is shown analytically that… (More)
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Highly Cited
2001
Highly Cited
2001
We describe a method to estimate the power spectral density of nonstationary noise when a noisy speech signal is given. The… (More)
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1997
1997
It has become increasingly accepted that wavelet based estimation techniques are generally better adapted to function estimates… (More)
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Highly Cited
1997
Highly Cited
1997
Communication Receivers offers a complete treatment on the theoretical and practical aspects of synchronization and channel… (More)
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