Parallelizable Bayesian tomography algorithms with rapid, guaranteed convergence

Bayesian tomographic reconstruction algorithms generally require the efficient optimization of a functional of many variables. In this setting, as well as in many other optimization tasks, functional substitution (FS) has been widely applied to simplify each step of the iterative process. The functi...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on image processing 2000-10, Vol.9 (10), p.1745-1759
Hauptverfasser:	Zheng, J., Saquib, S.S., Sauer, K., Bouman, C.A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Approximation theory Bayesian analysis Bayesian methods Computation Computational modeling Computer simulation Concurrent computing Convergence Convergence of numerical methods Descent Exact sciences and technology Function evaluation Image processing Image reconstruction Information, signal and communications theory Iterative algorithms Iterative methods Markov processes Mathematical analysis Mathematical models Parallel algorithms Parameter estimation Positron emission tomography Reconstruction algorithms Signal processing Studies Subspace constraints Telecommunications and information theory Tomography
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!