An adaptive regularized method for deconvolution of signals with edges by convex projections

Author

Sánchez-Avila, Carmen

Author_Institution

Dept. of Appl. Math., Ciudad Univ., Madrid, Spain

Volume

42

Issue

7

fYear

1994

fDate

7/1/1994 12:00:00 AM

Firstpage

1849

Lastpage

1851

Abstract

A new adaptive deconvolution method based on the projection operators onto convex sets (POCS) is presented. A minimum norm least-squares (MNLS) is obtained for signals with edges by means of an estimation-detection-protection scheme. The regularized differentiation technique is necessary for a reasonable detection of the signal edges. The improvement introduced with this method is illustrated through a simulation example. Finally, a discussion of the wide series of possibilities open along these lines closes this article

Keywords

differentiation; edge detection; least squares approximations; signal detection; signal processing; MNLS; POCS; adaptive deconvolution method; adaptive regularized method; convex projections; estimation-detection-protection scheme; minimum norm least-squares; projection operators onto convex sets; regularized differentiation; signal deconvolution; signal edges detection; simulation; Deconvolution; Digital signal processing; Iterative algorithms; Iterative methods; Seismology; Signal detection; Signal processing algorithms; Singular value decomposition; Speech coding; Wiener filter;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.298296

Filename

298296