منابع مشابه
Greedy Sparse Signal Recovery with Tree Pruning
Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Wellknown drawback of the greedy approach is that the chosen candidate is often not the optimal ...
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Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the theory of CS to include signals that are concisely represented in terms of a graphical model. In particular, we useMarkov Random Fields (MRFs) to represent sparse signals whose nonzero coefficients are clustered. Our new...
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Because of fast convergence in finite number of steps and low computational complexity, signal recovery from compressed measurements using greedy algorithms have generated a large amount of interest in recent years. Among these greedy algorithms OMP is well studied and recently its generalization, gOMP, have also drawn attention. On the other hand OLS and its generalization mOLS have been studi...
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ژورنال
عنوان ژورنال: The Journal of Korean Institute of Communications and Information Sciences
سال: 2014
ISSN: 1226-4717
DOI: 10.7840/kics.2014.39a.12.756