Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view
; Calderbank, A. R. C.
; Carin, L.
; Rodrigues , M.
Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view, Proc IEEE Global Conf. on Signal and Information Processing - Global SIP, Austin, Texas, United States, Vol. xx, pp. 628 - 628, December, 2013.
Digital Object Identifier: 0
Download Full text PDF ( 223 KBs)
We characterize the minimum number of measurements needed to drive to zero the minimum mean squared error (MMSE) of Gaussian mixture model (GMM) input signals in the low-noise regime. The result also hints at almost phase-transition optimal recovery procedures based on a classification and reconstruction approach.