Proximal Mappings Involving Almost Structured Matrices

Proximal Mappings Involving Almost Structured Matrices

We consider a minimization problem where the cost function consists of the sum of a quadratic data fidelity term and a penalty term. The quadratic involves a matrix H that can be embedded into a larger matrix H̃ where multiplication with the inverse of I + αH̃ T H̃ can be efficiently performed. We d...

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Veröffentlicht in:IEEE signal processing letters 2015-12, Vol.22 (12), p.2264-2268
1. Verfasser: Bayram, Ilker
Format: Artikel
Sprache:eng
Schlagworte:
Approximation algorithms
Circulant matrix
Context
Convergence
deconvolution
Dictionaries
Douglas-Rachford algorithm
Minimization
proximity operator
Signal processing algorithms
Sparse matrices
structured matrix
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Zusammenfassung:We consider a minimization problem where the cost function consists of the sum of a quadratic data fidelity term and a penalty term. The quadratic involves a matrix H that can be embedded into a larger matrix H̃ where multiplication with the inverse of I + αH̃ T H̃ can be efficiently performed. We discuss how to take advantage of this property when the Douglas-Rachford algorithm is utilized.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2015.2476381