7,621 research outputs found
Dynamical systems and forward-backward algorithms associated with the sum of a convex subdifferential and a monotone cocoercive operator
In a Hilbert framework, we introduce continuous and discrete dynamical
systems which aim at solving inclusions governed by structured monotone
operators , where is the subdifferential of a
convex lower semicontinuous function , and is a monotone cocoercive
operator. We first consider the extension to this setting of the regularized
Newton dynamic with two potentials. Then, we revisit some related dynamical
systems, namely the semigroup of contractions generated by , and the
continuous gradient projection dynamic. By a Lyapunov analysis, we show the
convergence properties of the orbits of these systems.
The time discretization of these dynamics gives various forward-backward
splitting methods (some new) for solving structured monotone inclusions
involving non-potential terms. The convergence of these algorithms is obtained
under classical step size limitation. Perspectives are given in the field of
numerical splitting methods for optimization, and multi-criteria decision
processes.Comment: 25 page
A forward-backward splitting algorithm for the minimization of non-smooth convex functionals in Banach space
We consider the task of computing an approximate minimizer of the sum of a
smooth and non-smooth convex functional, respectively, in Banach space.
Motivated by the classical forward-backward splitting method for the
subgradients in Hilbert space, we propose a generalization which involves the
iterative solution of simpler subproblems. Descent and convergence properties
of this new algorithm are studied. Furthermore, the results are applied to the
minimization of Tikhonov-functionals associated with linear inverse problems
and semi-norm penalization in Banach spaces. With the help of
Bregman-Taylor-distance estimates, rates of convergence for the
forward-backward splitting procedure are obtained. Examples which demonstrate
the applicability are given, in particular, a generalization of the iterative
soft-thresholding method by Daubechies, Defrise and De Mol to Banach spaces as
well as total-variation based image restoration in higher dimensions are
presented
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