article · 2010

Bayesian sequential compressed sensing in sparse dynamical systems

Christophe Andrieu, Robert Piechocki

Cited by 0Abstract and details only

Abstract

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 se-quential compressed sensing and develop methods to recursively estimate the full posterior distribution of the signal. I.

Cite this paper

APA 7

Andrieu, C., & Piechocki, R. (2010). Bayesian sequential compressed sensing in sparse dynamical systems.

MLA 9

Andrieu, Christophe, and Robert Piechocki. “Bayesian sequential compressed sensing in sparse dynamical systems.” 2010.

Chicago

Andrieu, Christophe, and Robert Piechocki. 2010. “Bayesian sequential compressed sensing in sparse dynamical systems.”

Harvard

Andrieu, C. and Piechocki, R. (2010) ‘Bayesian sequential compressed sensing in sparse dynamical systems’.

BibTeX

@article{andrieu2010bayesian,
  title = {{Bayesian sequential compressed sensing in sparse dynamical systems}},
  author = {Andrieu, Christophe and Piechocki, Robert},
  year = {2010}
}

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