Bayesian Inference and Compressed Sensing
Chapter
Published version
Permanent lenke
http://hdl.handle.net/11250/2491748Utgivelsesdato
2017Metadata
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- Institutt for lærerutdanning [3819]
- Publikasjoner fra CRIStin - NTNU [38525]
Originalversjon
10.5772/intechopen.70308Sammendrag
This chapter provides the use of Bayesian inference in compressive sensing (CS), a method in signal processing. Among the recovery methods used in CS literature, the convex relaxation methods are reformulated again using the Bayesian framework and this method is applied in different CS applications such as magnetic resonance imaging (MRI), remote sensing, and wireless communication systems, specifically on multiple-input multiple-output (MIMO) systems. The robustness of Bayesian method in incorporating prior information like sparse and structure among the sparse entries is shown in this chapter.