Refined Iterative Method for a Common Variational Inclusion and Common Fixed-Point Problem with Practical Applications

Abstract

This paper introduces a novel parallel method for solving common variational inclusion and common fixed-point (CVI-CFP) problems. The proposed algorithm provides a strong convergence theorem established under specific conditions associated with the CVI-CFP problem. Numerical simulations demonstrate the algorithm’s efficacy in the context of signal recovery problems involving various types of blurred filters. The results highlight the algorithm’s potential for practical applications in image processing and other fields.

Keywords

• process innovation
• common fixed-point problem
• common variational inclusion problem
• demicontractive mapping
• parallel method
• strong convergence