Title :
A Subband Adaptive Iterative Shrinkage/Thresholding Algorithm
Author :
Bayram, Ilker ; Selesnick, Ivan W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Polytech. Inst. of New York Univ., Brooklyn, NY, USA
fDate :
3/1/2010 12:00:00 AM
Abstract :
We investigate a subband adaptive version of the popular iterative shrinkage/thresholding algorithm that takes different update steps and thresholds for each subband. In particular, we provide a condition that ensures convergence and discuss why making the algorithm subband adaptive accelerates the convergence. We also give an algorithm to select appropriate update steps and thresholds for when the distortion operator is linear and time invariant. The results in this paper may be regarded as extensions of the recent work by Vonesch and Unser.
Keywords :
adaptive signal processing; iterative methods; convergence; linear distortion operator; subband adaptive iterative shrinkage; subband adaptive iterative thresholding; time invariant distortion operator; Deconvolution; fast algorithm; shrinkage; subband adaptive; thresholding; wavelet regularized inverse problem;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2009.2036064