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

Conference contribution
(Original article)


Publication Details

Author(s): Bereyhi A, Müller R
Publisher: IEEE
Publication year: 2018
Language: English


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 Authors / FAU Editors

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


External institutions
NTNU Trondheim - Norwegian University of Science and Technology


How to cite

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.

BibTeX: 

Last updated on 2018-22-09 at 15:21