DocumentCode
1155613
Title
Adaptive Least Squares for Parametric Spectral Estimation and Its Application to Pulse Estimation and Deconvolution of Seismic Data
Author
El-Sherief, Hossny
Volume
16
Issue
2
fYear
1986
fDate
3/1/1986 12:00:00 AM
Firstpage
299
Lastpage
303
Abstract
The method of recursive least squares, which has been used extensively in the field of system identification will be developed for adaptive parametric spectral estimation of digital signals. The method will be applied for adaptive pulse estimation and deconvolution of seismic data. Unlike the Levinson-type deconvolution method, the adaptive least-squares method does not need to estimate a priori the autocorrelation function and it avoids the windowing problem of a time-limited signal. Because of the recursive nature of the method, it is suitable for adaptive estimation and removal of time-varying pulses, and it is computationally simple and suitable for implementation on small computers with less memory requirements. The method has been implemented on different simulated examples, and the results are given and discussed.
Keywords
Autocorrelation; Chemicals; Computational modeling; Deconvolution; Distributed computing; Econometrics; Economic forecasting; Least squares approximation; Parametric statistics; Recursive estimation;
fLanguage
English
Journal_Title
Systems, Man and Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9472
Type
jour
DOI
10.1109/TSMC.1986.4308953
Filename
4308953
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