Convex Approaches to Model Wavelet Sparsity Patterns

Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees(HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing...

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Veröffentlicht in:	arXiv.org 2011-04
Hauptverfasser:	Rao, Nikhil S, Nowak, Robert D, Wright, Stephen J, Kingsbury, Nick G
Format:	Artikel
Sprache:	eng
Schlagworte:	Deconvolution Dependence Detection Graphical representations Inverse problems Iterative methods Markov analysis Markov chains Matrix methods Reconstruction Sparsity Wavelet analysis
Online-Zugang:	Volltext
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