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Paper detail

S-AMP for Non-linear Observation Models

Recently we extended Approximate message passing (AMP) algorithm to be able to handle general invariant matrix ensembles. In this contribution we extend our S-AMP approach to non-linear observation models. We obtain generalized AMP (GAMP) algorithm as the special case when the measurement matrix has zero-mean iid Gaussian entries. Our derivation is based upon 1) deriving expectation propagation (EP) like algorithms from the stationary-points equations of the Gibbs free energy under first- and second-moment constraints and 2) applying additive free convolution in free probability theory to get low-complexity updates for the second moment quantities.

preprint2015arXivOpen access
Burak ÇakmakOle WintherBernard H. Fleury
math.ITInformation Theory
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Burak ÇakmakOle WintherBernard H. Fleury

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