DocumentCode :
1385530
Title :
A property of the minimum vectors of a regularizing functional defined by means of the absolute norm
Author :
Alliney, Stefano
Author_Institution :
Dipt. di Matematica, Bologna Univ., Italy
Volume :
45
Issue :
4
fYear :
1997
fDate :
4/1/1997 12:00:00 AM
Firstpage :
913
Lastpage :
917
Abstract :
We consider a regularizing functional defined by means of the l 1 norm, where the regularization is obtained using first differences; as is well-known, such a functional can be put in relation with recursive median filters of appropriate window length. We show that at least one of the minima is reached at a vector, whose components have values over the same discrete set of the given signal. This suggests a simple method to refine the approximate solution to the regularization problem, which can be obtained with recursive median filters of increasing order. We also report an example of application, where the refinement method is employed for a signal detection problem
Keywords :
approximation theory; filtering theory; functional analysis; median filters; recursive filters; signal detection; absolute norm; approximate solution; l1 norm; minimum vectors; recursive median filters; refinement method; regularization problem; regularizing functional; signal detection; window length; Bayesian methods; Convolution; Filters; Mathematics; Maximum likelihood estimation; Parameter estimation; Signal detection; Signal processing; Signal processing algorithms; Vectors;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.564179
Filename :
564179
Link To Document :
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