Generalised Approximate Message Passing for Non-I.I.D. Sparse Signals

Christian Schou Oxvig, Thomas Arildsen

Research output: Contribution to conference without publisher/journalPosterResearch

Abstract

Generalised approximate message passing (GAMP) is an approximate Bayesian estimation algorithm for signals observed through a linear transform with a possibly non-linear measurement model.
By leveraging prior information about the observed signal, such as sparsity in a known dictionary, GAMP enables reconstructing signals from under-determined measurements – known as compressed sensing.
In the sparse signal setting, most existing signal priors for GAMP assume the input signal to have i.i.d. entries.
We present sparse signal priors to estimate non-identically distributed signals through a non-uniform weighting, e.g. enabling model-based compressed sensing with GAMP.
Original languageEnglish
Publication date22 Nov 2018
DOIs
Publication statusPublished - 22 Nov 2018
Eventinternational Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques - Centre International de Rencontres Mathématiques, Marseille, France
Duration: 21 Nov 201823 Nov 2018
Conference number: 4
https://sites.google.com/view/itwist18

Workshop

Workshopinternational Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques
Number4
LocationCentre International de Rencontres Mathématiques
CountryFrance
CityMarseille
Period21/11/201823/11/2018
Internet address

Fingerprint

Message passing
Compressed sensing
Glossaries

Keywords

  • compressed sensing
  • signal processing
  • estimation theory

Cite this

Oxvig, C. S., & Arildsen, T. (2018). Generalised Approximate Message Passing for Non-I.I.D. Sparse Signals. Poster session presented at international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Marseille, France. https://doi.org/10.5281/zenodo.1690664
Oxvig, Christian Schou ; Arildsen, Thomas. / Generalised Approximate Message Passing for Non-I.I.D. Sparse Signals. Poster session presented at international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Marseille, France.
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Generalised Approximate Message Passing for Non-I.I.D. Sparse Signals. / Oxvig, Christian Schou; Arildsen, Thomas.

2018. Poster session presented at international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Marseille, France.

Research output: Contribution to conference without publisher/journalPosterResearch

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Oxvig CS, Arildsen T. Generalised Approximate Message Passing for Non-I.I.D. Sparse Signals. 2018. Poster session presented at international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques, Marseille, France. https://doi.org/10.5281/zenodo.1690664