Creating and sharing knowledge for telecommunications

Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view

Renna, F. ; 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)

Abstract
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.