# Spectral density estimation

## Papers overview

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Highly Cited

2017

Highly Cited

2017

- IEEE Transactions on Signal Processing
- 2017

Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domainâ€¦Â (More)

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2015

2015

- 2015

We develop a Bayesian modelling approach for spectral densities, built from a local Gaussian mixture approximation to the Whittleâ€¦Â (More)

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Highly Cited

2011

Highly Cited

2011

- IEEE International Conference on Acousticsâ€¦
- 2011

In this paper, we consider power spectral density estimation of bandlimited, wide-sense stationary signals from sub-Nyquistâ€¦Â (More)

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2011

2011

- 2011

Traditional kernel spectral density estimators are linear as a function of the sample autocovariance sequence. The purpose of theâ€¦Â (More)

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2011

2011

- ISSCS - International Symposium on Signalsâ€¦
- 2011

The power spectral density of a signal can be estimated most accurately by using a window with a narrow bandwidth and largeâ€¦Â (More)

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2009

2009

- IEEE International Conference on Acousticsâ€¦
- 2009

Self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. In this paperâ€¦Â (More)

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2007

2007

- IEEE Transactions on Signal Processing
- 2007

This correspondence introduces the use of sharpened periodograms for spectral density estimation. It is shown analytically thatâ€¦Â (More)

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Highly Cited

2001

Highly Cited

2001

- IEEE Trans. Speech and Audio Processing
- 2001

We describe a method to estimate the power spectral density of nonstationary noise when a noisy speech signal is given. Theâ€¦Â (More)

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1997

1997

- Conference Record of the Thirty-First Asilomarâ€¦
- 1997

It has become increasingly accepted that wavelet based estimation techniques are generally better adapted to function estimatesâ€¦Â (More)

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Highly Cited

1997

Highly Cited

1997

- 1997

Communication Receivers offers a complete treatment on the theoretical and practical aspects of synchronization and channelâ€¦Â (More)

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