Split convex minimization algorithm for signal recovery

A broad range of signal recovery problems can be abstracted into the problem of minimizing the sum of several convex functions in a Hilbert space. We propose a proximal decomposition algorithm which, under mild conditions, provides a solution to such a problem. A significant improvement over the met...

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Bibliographische Detailangaben
Hauptverfasser:	Combettes, P.L., Pesquet, J.-C.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Convergence convex optimization methods Data acquisition Hilbert space Image restoration Inverse problems Minimization methods Optimization methods parallel algorithm Parallel algorithms Signal restoration variational methods Wavelet transforms
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Beschreibung
Zusammenfassung:	A broad range of signal recovery problems can be abstracted into the problem of minimizing the sum of several convex functions in a Hilbert space. We propose a proximal decomposition algorithm which, under mild conditions, provides a solution to such a problem. A significant improvement over the methods currently in use in the area of signal recovery is that it is not limited to two nondifferentiable functions. An application to image restoration is demonstrated.
ISSN:	1520-6149 2379-190X
DOI:	10.1109/ICASSP.2009.4959676