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A sparse adaptive filtering using time-varying soft-thresholding techniques
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
In this paper, we propose a novel adaptive filtering algorithm based on an iterative use of (i) the proximity operator and (ii) the parallel variable-metric projection. Our time-varying cost function is a weighted sum of squared distances (in a variable-metric sense) plus a possibly nonsmooth penalty term, and the proposed algorithm is derived along the idea of proximal forward-backward splitting in convex analysis. For application to sparse-system identification problems, we employ thedoi:10.1109/icassp.2010.5495870 dblp:conf/icassp/MurakamiYYY10 fatcat:majw2dw3cfaqdb6ciuc4kp3in4