PHASE-SENSITIVE DECONVOLUTION TO MODEL RANDOM PROCESSES, WITH SPECIAL REFERENCE TO ASTRONOMICAL DATA**Some of this material is extracted from a tutorial monograph (Scargle, 1979), a revision of which will appear in the Astrophysical Journal Supplements.-Reference-Cited by-同舟云学术

PHASE-SENSITIVE DECONVOLUTION TO MODEL RANDOM PROCESSES, WITH SPECIAL REFERENCE TO ASTRONOMICAL DATA**Some of this material is extracted from a tutorial monograph (Scargle, 1979), a revision of which will appear in the Astrophysical Journal Supplements.

Published:1981 Issue: Volume: Page:549-564
ISSN:
Container-title:Applied Time Series Analysis II
language:
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Author:

Scargle Jeffrey D.

Publisher

Elsevier

Reference16 articles.

1. “Stastical Predictor Identification,”;Akaike;Ann. Inst. Statist. Math.,1970

2. “Robust Identification of a Nonminimum Phase System: Blind Adjustment of a Linear Equalizer in Data Communications,”;Benveniste;I.E.E.E. Transactions on Automatic Control,1980

3. Stochastic Processes;Doob,1953

4. “Non-Linear Time Series Modelling,”;Granger,1978

5. “On the Representation Problem for Stationary Stochastic Processes with Trivial Tail Fields,”;Hanson;Journal of Mathematics and Mechanics,1963

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