Linear and strong convergence of algorithms involving averaged nonexpansive operators-Reference-Cited by-同舟云学术

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Linear and strong convergence of algorithms involving averaged nonexpansive operators

Published:2015-01 Issue:1 Volume:421 Page:1-20
ISSN:0022-247X
Container-title:Journal of Mathematical Analysis and Applications
language:en
Short-container-title:Journal of Mathematical Analysis and Applications

Author:

Bauschke Heinz H.,Noll Dominikus,Phan Hung M.

Funder

Natural Sciences and Engineering Research Council of Canada

Canada Research Chair Program

Pacific Institute of the Mathematical Sciences

NSERC

Publisher

Elsevier BV

Subject

Applied Mathematics,Analysis

Reference28 articles.

1. Convergence of the proximal point method for metrically regular mappings;Aragón Artacho;ESAIM Proc.,2007

2. A norm convergence result on random products of relaxed projections in Hilbert space;Bauschke;Trans. Amer. Math. Soc.,1995

3. Projection algorithms and monotone operators;Bauschke,1996

4. The rate of linear convergence of the Douglas–Rachford algorithm for subspaces is the cosine of the Friedrichs angle;Bauschke;J. Approx. Theory,2014

5. On the convergence of von Neumann's alternating projection algorithm for two sets;Bauschke;Set-Valued Anal.,1993

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