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Cited by 4,418

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Spectrum estimation and harmonic analysis

Thomson, D.J.·1982·Proceedings of the IEEE

Abstract

In the choice of an estimator for the spectrum of a stationary time series from a finite sample of the process, the problems of bias control and consistency, or "smoothing," are dominant. In this paper we present a new method based on a "local" eigenexpansion to estimate the spectrum in terms of the solution of an integral equation. Computationally this method is equivalent to using the weishted average of a series of direct-spectrum estimates based on orthogonal data windows (discrete prolate spheroidal sequences) to treat both the bias and smoothing problems. Some of the attractive features of this estimate are: there are no arbitrary windows; it is a small sample theory; it is consistent; it provides an analysis-of-variance test for line components; and it has high resolution. We also show relations of this estimate to maximum-likelihood estimates, show that the estimation capacity of the estimate is high, and show applications to coherence and polyspectrum estimates.

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Metadata

Authors
Thomson, D. J.
Venue
Proceedings of the IEEE
Published
1982
Volume
70
Issue
9
Pages
1055-1096
ISSN
0018-9219 (ISSN-L)
OpenAlex
W2155722796
Cited by
4,418
References
5
FWCI
8.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Spectrum estimation and harmonic analysis. https://app.cochat.ai/papers/10.1109/proc.1982.12433
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Thomson, D. J. (1982). Spectrum estimation and harmonic analysis. Proceedings of the IEEE. https://doi.org/10.1109/proc.1982.12433

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