Minimization of Non-smooth, Non-convex Functionals by Iterative Thresholding

Convergence analysis is carried out for a forward-backward splitting/generalized gradient projection method for the minimization of a special class of non-smooth and genuinely non-convex minimization problems in infinite-dimensional Hilbert spaces. The functionals under consideration are the sum of...

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Veröffentlicht in:	Journal of optimization theory and applications Jg. 165; H. 1; S. 78 - 112
Hauptverfasser:	Bredies, Kristian, Lorenz, Dirk A., Reiterer, Stefan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.04.2015 Springer Nature B.V
Schlagworte:	Algebra Algorithms Applications of Mathematics Calculus of Variations and Optimal Control; Optimization Convergence Convex analysis Data recovery Engineering Functionals Hilbert space Inverse problems Iterative methods Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Methods Minimization Operations Research/Decision Theory Optimization Partial differential equations Projection Splitting Studies Theory of Computation Gradient projection method 65K10 Non-convex optimization Iterative thresholding 49M05 Non-smooth optimization
ISSN:	0022-3239, 1573-2878
Online-Zugang:	Volltext
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