A Dual Approach to Linear Inverse Problems with Convex Constraints

DOI10.1137/0331049zbMath0797.49019OpenAlexW2024855591MaRDI QIDQ3138085

Lee C. Potter, K. S. Arun

Publication date: 6 December 1993

Published in: SIAM Journal on Control and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/0331049

zbMATH Keywords

fixed point iteration

Mathematics Subject Classification ID

Convex programming (90C25) Optimality conditions for problems in abstract spaces (49K27)

Related Items (13)

Mann type iterative methods for finding a common solution of split feasibility and fixed point problems ⋮ An implementable splitting algorithm for the \(\ell_1\)-norm regularized split feasibility problem ⋮ Proximal Splitting Methods in Signal Processing ⋮ The Mann-type extragradient iterative algorithms with regularization for solving variational inequality problems, split feasibility, and fixed point problems ⋮ Relaxed extragradient methods with regularization for general system of variational inequalities with constraints of split feasibility and fixed point problems ⋮ Dualization of signal recovery problems ⋮ Some modified extragradient methods for solving split feasibility and fixed point problems ⋮ Relaxed and hybrid viscosity methods for general system of variational inequalities with split feasibility problem constraint ⋮ An extragradient method for solving split feasibility and fixed point problems ⋮ Proximity for sums of composite functions ⋮ A strongly convergent method for the split feasibility problem ⋮ Duality and Convex Programming ⋮ Multiplicative Algorithms for Maximum Penalized Likelihood Inversion with Non Negative Constraints and Generalized Error Distributions

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