Generalized approximate message passing for estimation with random linear mixing
Published: Jul 1, 2011
Abstract
We consider the estimation of a random vector observed through a linear transform followed by a componentwise probabilistic measurement channel. Although such linear mixing estimation problems are generally highly non-convex, Gaussian approximations of belief propagation (BP) have proven to be computationally attractive and highly effective in a range of applications. Recently, Bayati and Montanari have provided a rigorous and extremely general...
Paper Details
Title
Generalized approximate message passing for estimation with random linear mixing
Published Date
Jul 1, 2011
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