Results 1  10
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156
based on the Periodogram
, 1995
"... The method of surrogate data is a tool to test whether data were generated by some class of model. Tests based on the periodogram have been proposed to decide if linear systems driven by Gaussian noise could have generated a sample time series. We show that this procedure based on the periodogram, i ..."
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The method of surrogate data is a tool to test whether data were generated by some class of model. Tests based on the periodogram have been proposed to decide if linear systems driven by Gaussian noise could have generated a sample time series. We show that this procedure based on the periodogram
Assessing statistical significance of periodogram peaks
, 711
"... Analysing astronomical time series, one often has to choose between at least two hypotheses, a base one H and an alternative one K, based on the existing data array. In the signal detection problem, one should check whether the observations ..."
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Cited by 2 (2 self)
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Analysing astronomical time series, one often has to choose between at least two hypotheses, a base one H and an alternative one K, based on the existing data array. In the signal detection problem, one should check whether the observations
Bayesian Interpretation of Periodograms
 IEEE Trans. Signal Processing
, 1988
"... The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid to their interpretation with ..."
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Cited by 4 (2 self)
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The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid to their interpretation
Generalizing the LombScargle Periodogram
"... This paper is an elaboration of an issue that arose in the paper "Nonuniform Sampling: Bandwidth and Aliasing" [1]. In that paper the single frequency estimation problem was explored using Bayesian probability theory for quadrature data that were sampled nonuniformly and nonsimultaneously. ..."
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Cited by 1 (0 self)
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. In the process of discussing single frequency estimation, it was shown that the LombScargle periodogram is the sufficient statistic for single frequency estimation for a stationary sinusoid given real nonuniformly sampled data. Here we demonstrate that the LombScargle periodogram may be generalized in a
UP Usual periodogram.
"... Abstract—The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid to their interpretation ..."
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to their interpretation within the Bayesian statistical framework. Finally, the question of unsupervised hyperparameter and window selection is addressed. It is shown that maximum likelihood solution is both formally achievable and practically useful. Index Terms—Hyperparameters, penalized criterion, periodograms
UP Usual Periodogram
, 908
"... Abstract — The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid to their interpretati ..."
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Abstract — The usual nonparametric approach to spectral analysis is revisited within the regularization framework. Both usual and windowed periodograms are obtained as the squared modulus of the minimizer of regularized least squares criteria. Then, particular attention is paid
Tests of Bias in LogPeriodogram Regression
"... This paper proposes simple Hausmantype tests to check for bias in the logperiodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the null hypothesis that no bias is present, and the tests are consistent. ..."
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Cited by 7 (4 self)
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This paper proposes simple Hausmantype tests to check for bias in the logperiodogram regression of a time series believed to be long memory. The statistics are asymptotically standard normal on the null hypothesis that no bias is present, and the tests are consistent.
BAYESIAN PERIODOGRAM SMOOTHING FOR SPEECH ENHANCEMENT
"... Abstract. Periodogram smoothing of the received noisy signal is a challenging problem in speech enhancement. We present a Bayesian approach, where the instantaneous periodogram is smoothed through an adaptive smoothing parameter. By updating sufficient statistics using new samples of the noisy signa ..."
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Abstract. Periodogram smoothing of the received noisy signal is a challenging problem in speech enhancement. We present a Bayesian approach, where the instantaneous periodogram is smoothed through an adaptive smoothing parameter. By updating sufficient statistics using new samples of the noisy
Residual logperiodogram inference for long run relationships
, 2002
"... We assume that some consistent estimator bβ of an equilibrium relation between nonstationary series integrated of order d ∈ (0.5, 1.5) is used to compute residuals ût = yt −bβxt (or differences thereof). We propose to apply the semiparametric logperiodogram regression to the (differenced) residual ..."
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Cited by 21 (3 self)
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We assume that some consistent estimator bβ of an equilibrium relation between nonstationary series integrated of order d ∈ (0.5, 1.5) is used to compute residuals ût = yt −bβxt (or differences thereof). We propose to apply the semiparametric logperiodogram regression to the (differenced
The Stationary Wavelet Transform and some Statistical Applications
, 1995
"... Wavelets are of wide potential use in statistical contexts. The basics of the discrete wavelet transform are reviewed using a filter notation that is useful subsequently in the paper. A `stationary wavelet transform', where the coefficient sequences are not decimated at each stage, is described ..."
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Cited by 177 (19 self)
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Wavelets are of wide potential use in statistical contexts. The basics of the discrete wavelet transform are reviewed using a filter notation that is useful subsequently in the paper. A `stationary wavelet transform', where the coefficient sequences are not decimated at each stage
Results 1  10
of
156