# Using prior support information in approximate message passing algorithms

 Title Using prior support information in approximate message passing algorithms Publication Type SINBAD Presentation Authors Navid Ghadermarzy, Ozgur Yilmaz, Felix J. Herrmann Publisher SINBAD Year of Publication 2013 Abstract Consider the standard compressed sensing problem. We want to recover sparse compressible aorsignal from few linear measurements. In this talk we investigate recovery performance when we have prior information about the support, i.e., the indices of the non-zero entries, of the signal to be recovered. First we briefly review the results of "weighted $\ell_p$ minimization algorithm with p = 1 and 0 < p < 1". Then we derive a weighted approximate message passing (AMP) algorithm which incorporates prior support information into the AMP algorithm. We empirically show that this algorithm recovers sparse signals significantly faster than weighted $\ell_1$ minimization. We also introduce a reweighting scheme for AMP and weighted AMP which, we observe, substantially improves the recovery conditions of these algorithms. We illustrate our results with extensive numerical experiments on synthetic data and seismic data reconstruction. Keywords Presentation, private, SINBAD, SINBADFALL2013, SLIM URL https://www.slim.eos.ubc.ca/Publications/Private/Conferences/SINBAD/2013/Fall/ghadermarzy2013SINBADups/ghadermarzy2013SINBADups.pdf Citation Key ghadermarzy2013SINBADups