Abstract
AbstractThe purpose of the paper is to study the proximal split feasibility problems. For solving the problems, we present new self-adaptive algorithms with the regularization technique. By using these algorithms, we give some strong convergence theorems for the proximal split feasibility problems.
Highlights
The split feasibility problem has received much attention due to its applications in signal processing and image reconstruction [ ] with particular progress in intensity modulated therapy [ ]
We focus on the following minimization problem: min f x† + gλ Ax†, ( . )
We introduce two lemmas for our main results in this paper
Summary
The split feasibility problem has received much attention due to its applications in signal processing and image reconstruction [ ] with particular progress in intensity modulated therapy [ ]. Our purpose of the present manuscript is to study the more general case of the proximal split minimization problems by introducing new algorithms with the regularization technique.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
