Maximum-A-Posteriori Signal Recovery with Prior Information: Applications to Compressive Sensing

Beitrag bei einer Tagung
(Originalarbeit)


Details zur Publikation

Autor(en): Bereyhi A, Müller R
Verlag: IEEE
Jahr der Veröffentlichung: 2018
Sprache: Englisch


Abstract

This paper studies the asymptotic performance of maximum-a-posteriori
estimation in the presence of prior information. The problem arises in several
applications such as recovery of signals with non-uniform sparsity pattern from
underdetermined measurements. With prior information, the maximum-a-posteriori
estimator might have asymmetric penalty. We consider a generic form of this
estimator and study its performance via the replica method. Our analyses
demonstrate an asymmetric form of the decoupling property in the large-system
limit. Employing our results, we further investigate the performance of
weighted zero-norm minimization for recovery of a non-uniform sparse signal.
Our investigations illustrate that for a given distortion, the minimum number
of required measurements can be significantly reduced by choosing weighting
coefficients optimally.


FAU-Autoren / FAU-Herausgeber

Bereyhi, Ali
Lehrstuhl für Digitale Übertragung
Müller, Ralf Prof. Dr.-Ing.
Professur für Informationsübertragung


Zitierweisen

APA:
Bereyhi, A., & Müller, R. (2018). Maximum-A-Posteriori Signal Recovery with Prior Information: Applications to Compressive Sensing. Alberta, CA: IEEE.

MLA:
Bereyhi, Ali, and Ralf Müller. "Maximum-A-Posteriori Signal Recovery with Prior Information: Applications to Compressive Sensing." Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Alberta IEEE, 2018.

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Zuletzt aktualisiert 2018-22-09 um 15:21