Conference item
Bayesian sequential compressed sensing in sparse dynamical systems
- Abstract:
- While the theory of compressed sensing provides means to reliably and efficiently acquire a sparse high-dimensional signal from a small number of its linear projections, sensing of dynamically changing sparse signals is still not well understood.We pursue a Bayesian approach to the problem of sequential compressed sensing and develop methods to recursively estimate the full posterior distribution of the signal. ©2010 IEEE.
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Bibliographic Details
- Host title:
- 2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
- Pages:
- 1730-1736
- Publication date:
- 2010-01-01
- DOI:
- ISBN:
- 9781424482146
Item Description
- Pubs id:
-
pubs:487763
- UUID:
-
uuid:07481a77-69cf-44f0-b4b6-f0ae022587c6
- Local pid:
- pubs:487763
- Source identifiers:
-
487763
- Deposit date:
- 2014-11-11
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- Copyright date:
- 2010
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