Minimum-variance deconvolution for noncausal wavelets

Author

Yu, Tie-Jun ; Muller, Peter C. ; Dai, Guan-Zhong ; Lin, Ching-Fang

Author_Institution

Dept. of Autom. Control, Northwestern Polytech. Univ., Xian, China

Volume

32

Issue

3

fYear

1994

fDate

5/1/1994 12:00:00 AM

Firstpage

513

Lastpage

524

Abstract

Deconvolution is an important technique in data processing. At present, there have been a lot of publications on deconvolution problems. Most of them are only applicable to causal wavelets. In this paper the minimum-variance deconvolution for noncausal wavelets are studied. First, an equivalent recursive model to the convolutional sum model for noncausal wavelets is set up. This recursive model is a descriptor model with two-point boundary conditions. Second, using the estimation theory of two-point boundary value systems, the minimum-variance estimator of input or reflection is presented and the corresponding implementation procedures of the input estimator and the estimation error variance are derived. Finally, examples are provided that illustrate the performance of the algorithms in this paper

Keywords

geophysical techniques; seismology; algorithm; convolutional sum model; data processing; descriptor model; equivalent recursive model; geophysical measurement technique; minimum variance deconvolution; noncausal wavelet; seismology; two-point boundary conditions; Absorption; Boundary conditions; Convolution; Data processing; Deconvolution; Estimation theory; Filters; Reflection; Senior members; Signal processing algorithms;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.297970

Filename

297970