A fast matching pursuit method (nGpFBMP) is introduced which performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian/unknown. It is agnostic on signal statistics and utilizes a greedy approach and order-recursive updates to determine the approximate MMSE estimate of the sparse signal. Simulation results demonstrate the power and robustness of the method.
|Original language||English (US)|
|Title of host publication||15th. Saudi Technical Exchange Meeting (STEM)|
|State||Published - Dec 2012|