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Strong convergence of inertial forward–backward methods for solving monotone inclusions

Bing Tan, Sun Young Cho

2021Applicable Analysis57 citationsDOI

Abstract

The paper presents four modifications of the inertial forward–backward splitting method for monotone inclusion problems in the framework of real Hilbert spaces. The advantages of our iterative schemes are that the single-valued operator is Lipschitz continuous monotone rather than cocoercive and the Lipschitz constant does not require to be known. The strong convergence of the suggested approaches is obtained under some standard and mild conditions. Finally, several numerical experiments in finite- and infinite-dimensional spaces are proposed to demonstrate the advantages of our algorithms over the existing related ones.

Topics & Concepts

Lipschitz continuityMonotone polygonMathematicsHilbert spaceConvergence (economics)Inertial frame of referenceApplied mathematicsStrongly monotoneOperator (biology)Constant (computer programming)Scheme (mathematics)Mathematical analysisComputer scienceGeometryChemistryTranscription factorGeneProgramming languageRepressorBiochemistryQuantum mechanicsPhysicsEconomicsEconomic growthNumerical methods in inverse problemsOptimization and Variational AnalysisAdvanced Optimization Algorithms Research
Strong convergence of inertial forward–backward methods for solving monotone inclusions | Litcius