- Title
- On projection algorithms for solving convex feasibility problems
- Creator
- Bauschke, Heinz H.; Borwein, Jonathan M.
- Relation
- SIAM Review Vol. 38, Issue 3, p. 367-426
- Publisher Link
- http://dx.doi.org/10.1137/S0036144593251710
- Publisher
- Society for Industrial and Applied Mathematics (SIAM)
- Resource Type
- journal article
- Date
- 1996
- Description
- Due to their extraordinary utility and broad applicability in many areas of classical mathematics and modern physical sciences (most notably, computerized tomography), algorithms for solving convex feasibility problems continue to receive great attention. To unify, generalize, and review some of these algorithms, a very broad and flexible framework is investigated. Several crucial new concepts which allow a systematic discussion of questions on behaviour in general Hilbert spaces and on the quality of convergence are brought out. Numerous examples are given.
- Subject
- angle between two subspaces; averaged mapping; firmly nonexpansive mapping; Hilbert space; image recovery; iterative method; Kaczmarz’s method; linear convergence; linear feasibility problem; linear inequalities; nonexpansive mapping; orthogonal projection; Cimmino’s method; projection algorithm; projection method; Slater point; subdifferential; subgradient; subgradient algorithm; successive projections; computerized tomography; convex feasibility problem; convex function; convex inequalities; convex programming; convex set; Fejer monotone sequence
- Identifier
- http://hdl.handle.net/1959.13/940478
- Identifier
- uon:13019
- Identifier
- ISSN:0036-1445
- Language
- eng
- Full Text
- Reviewed
- Hits: 5579
- Visitors: 6589
- Downloads: 1062
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Publisher version (open access) | 6 MB | Adobe Acrobat PDF | View Details Download |