منابع مشابه
Frames for compressed sensing using coherence
We give some new results on sparse signal recovery in the presence of noise, for weighted spaces. Traditionally, were used dictionaries that have the norm equal to 1, but, for random dictionaries this condition is rarely satised. Moreover, we give better estimations then the ones given recently by Cai, Wang and Xu.
متن کاملframes for compressed sensing using coherence
we give some new results on sparse signal recovery in the presence of noise, forweighted spaces. traditionally, were used dictionaries that have the norm equal to 1, but, forrandom dictionaries this condition is rarely satis ed. moreover, we give better estimationsthen the ones given recently by cai, wang and xu.
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The field of compressed sensing has shown that a sparse but otherwise arbitrary vector can be recovered exactly from a small number of randomly constructed linear projections (or samples). The question addressed in this paper is whether an even smaller number of samples is sufficient when there exists prior knowledge about the distribution of the unknown vector, or when only partial recovery is...
متن کاملCompressed Counting Meets Compressed Sensing
Compressed1 sensing (sparse signal recovery) has been a popular and important research topic in recent years. By observing that natural signals are often nonnegative, we propose a new framework for nonnegative signal recovery using Compressed Counting (CC). CC is a technique built on maximally-skewed α-stable random projections originally developed for data stream computations. Our recovery pro...
متن کاملCompressed Sensing
Compressed sensing is an exciting, rapidly growing field which has attracted considerable attention in electrical engineering, applied mathematics, statistics, and computer science. Since its initial introduction several years ago an avalanche of results have been obtained both of a theoretical as well as practical nature, and various conferences, workshops, and special sessions have been dedic...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2013
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2013.2254172