Abstract
We propose a novel iterative estimation algorithm for linear observation models called S-AMP. The fixed points of
S-AMP are the stationary points of the exact Gibbs free energy under a set of (first- and second-) moment consistency constraints
in the large system limit. S-AMP extends the approximate message-passing (AMP) algorithm to general matrix ensembles
with a well-defined large system size limit. The generalization is based on the S-transform (in free probability) of the spectrum
of the measurement matrix. Furthermore, we show that the optimality of S-AMP follows directly from its design rather than
from solving a separate optimization problem as done for AMP.
S-AMP are the stationary points of the exact Gibbs free energy under a set of (first- and second-) moment consistency constraints
in the large system limit. S-AMP extends the approximate message-passing (AMP) algorithm to general matrix ensembles
with a well-defined large system size limit. The generalization is based on the S-transform (in free probability) of the spectrum
of the measurement matrix. Furthermore, we show that the optimality of S-AMP follows directly from its design rather than
from solving a separate optimization problem as done for AMP.
| Original language | English |
|---|---|
| Title of host publication | Information Theory Workshop (ITW), 2014 IEEE |
| Number of pages | 5 |
| Publisher | IEEE Press |
| Publication date | 2 Nov 2014 |
| Pages | 192 - 196 |
| ISBN (Electronic) | 978-1-4799-5998-0 |
| DOIs | |
| Publication status | Published - 2 Nov 2014 |
| Event | 2014 IEEE Information Theory Workshop - Hobart, Australia Duration: 2 Nov 2014 → 5 Nov 2014 Conference number: 32406 |
Conference
| Conference | 2014 IEEE Information Theory Workshop |
|---|---|
| Number | 32406 |
| Country/Territory | Australia |
| City | Hobart |
| Period | 02/11/2014 → 05/11/2014 |
| Series | IEEE Information Theory Workshop |
|---|---|
| ISSN | 1662-9019 |