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Compressive Sensing

by Rauhut Holger, Massimo Fornasier

Abstract

Compressive sensing is a new type of sampling theory, which pre- dicts that sparse signals and images can be reconstructed from what was previously believed to be incomplete information. As a main fea- ture, efficient algorithms such as ℓ1-minimization can be used for recov- ery. The theory has many potential applications in signal processing and imaging. This chapter gives an introduction and overview on both theoretical and numerical aspects of compressive sensing.

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