phil schniter: EM-turbo-GAMP matlab code

EM-turbo-GAMP matlab code

The following links point to matlab code for sparse reconstruction (i.e., compressive sensing) of a single measurement vector (SMV) or multiple measurement vectors (MMV). All of these techniques build on the Generalized Approximate Message Passing (GAMP) algorithm, developed by Sundeep Rangan for the case of known i.i.d signal and noise priors. The code below extends GAMP to the practical case of unknown non-i.i.d priors by automatically learning the signal and noise prior parameters (while simultaneously reconstructing the signal) using an Expectation Maximization (EM) approach, and by incorporating structured sparsity using the turbo-GAMP approach, where the hyperparameters behind the structured-sparsity are also learned using EM.

o matlab code

o references

o background literature

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(last updated Thursday, 26-Feb-2015 14:58:03 EST)