New self-adaptive step size algorithms for solving split variational inclusion problems and its applications

In this paper, we study a special instance of the split inverse problem (SIP), which is the split variational inclusion problem (SVIP). Three simple iterative methods for solving it are introduced and weak and strong convergence theorems are established under mild and standard assumptions. As an app...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Numerical algorithms Ročník 83; číslo 1; s. 305 - 331
Hlavní autori: Tang, Yan, Gibali, Aviv
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.01.2020
Springer Nature B.V
Predmet:
Adaptive algorithms
Algebra
Algorithms
Computer Science
Continuity (mathematics)
Data compression
Feasibility
Inverse problems
Iterative methods
Mathematical analysis
Mathematics
Numeric Computing
Numerical Analysis
Original Paper
Theory of Computation
Self-adaptive
Strong convergence
Split variational inclusion problem
Convex minimization problems
ISSN:1017-1398, 1572-9265
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this paper, we study a special instance of the split inverse problem (SIP), which is the split variational inclusion problem (SVIP). Three simple iterative methods for solving it are introduced and weak and strong convergence theorems are established under mild and standard assumptions. As an application, the problem of minimizing two proper, convex, and lower semi-continuous functions is considered. We compare and illustrate the efficiency and applicability of our schemes for several numerical experiments as well as an example in the field of compressed sensing.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1017-1398
1572-9265
DOI:10.1007/s11075-019-00683-0