Journal ArticleDOI
Estimating the number of sinusoids in additive white noise
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The test proposed uses the eigenvector decomposition of the estimated autocorrelation matrix and is based on matrix perturbation analysis and is shown to be able to resolve closely spaced sinusoids at lower signal-to-noise ratios than heuristic tests.Abstract:
The test proposed uses the eigenvector decomposition of the estimated autocorrelation matrix and is based on matrix perturbation analysis. The estimator is shown to be able to resolve closely spaced sinusoids at lower signal-to-noise ratios than heuristic tests. Simulation results for two closely spaced sinusoids are detailed. Several unanswered questions are discussed. >read more
Citations
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Book
Spectral analysis of signals
Petre Stoica,Randolph L. Moses +1 more
TL;DR: 1. Basic Concepts. 2. Nonparametric Methods. 3. Parametric Methods for Rational Spectra.
Journal ArticleDOI
A least-squares approach to blind channel identification
TL;DR: A new blind identification algorithm based solely on the system outputs is proposed and necessary and sufficient identifiability conditions in terms of the multichannel systems and the deterministic input signal are presented.
Journal ArticleDOI
Model based processing of signals: a state space approach
Bhaskar D. Rao,K.S. Arun +1 more
TL;DR: In this paper, a tutorial on linear, state space, model-based methods for certain nonlinear estimation problems commonly encountered in signal and data analysis is presented. But the approach is applicable to a vast range of nonlinear signal analysis problems and applications in direction finding and damped sinusoid retrieval are dealt with in detail.
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Multi-Pitch Estimation
TL;DR: An introduction to pitch estimation is given and a number of statistical methods for pitch estimation are presented, which include both single- and multi-pitch estimators based on statistical approaches, filtering methods based on both static and optimal adaptive designs, and subspace methodsbased on the principles of subspace orthogonality and shift-invariance.
Journal ArticleDOI
Statistical analysis of MUSIC and subspace rotation estimates of sinusoidal frequencies
Petre Stoica,Torsten Söderström +1 more
TL;DR: Consideration is given to the analysis of the large-sample second-order properties of multiple signal classification (MUSIC) and subspace rotation (SUR) methods, such as ESPRIT, for sinusoidal frequency estimation.
References
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Journal ArticleDOI
Detection of signals by information theoretic criteria
Mati Wax,Thomas Kailath +1 more
TL;DR: Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented.
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The Retrieval of Harmonics from a Covariance Function
TL;DR: In this paper, a new method for retrieving harmonics from a covariance function is introduced, based on a theorem of Caratheodory about the trigonometrical moment problem.
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Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihood
Donald W. Tufts,Ramdas Kumaresan +1 more
TL;DR: In this paper, the frequency estimation performance of the forward-backward linear prediction (FBLP) method was improved for short data records and low signal-to-noise ratio (SNR) by using information about the rank M of the signal correlation matrix.
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Spectral estimation: An overdetermined rational model equation approach
TL;DR: In this paper, it is shown that by taking this overdetermined parametric evaluation approach, a reduction in data-induced model parameter hypersensitivity is obtained, and a corresponding improvement in modeling performance results.
Journal ArticleDOI
High performance spectral estimation--A new ARMA method
TL;DR: In this article, a method for generating an ARMA model spectral estimate of a wide-sense stationary time series from a finite set of observations is presented, which is based upon a set of error equations which are dependent on the model's parameters.