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Dynamical Functional Theory for Compressed Sensing
[article]
2017
arXiv
pre-print
We introduce a theoretical approach for designing generalizations of the approximate message passing (AMP) algorithm for compressed sensing which are valid for large observation matrices that are drawn from an invariant random matrix ensemble. By design, the fixed points of the algorithm obey the Thouless-Anderson-Palmer (TAP) equations corresponding to the ensemble. Using a dynamical functional approach we are able to derive an effective stochastic process for the marginal statistics of a
arXiv:1705.04284v1
fatcat:l7ce7rfjezhgzfz7gkglniilfy