Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view
Publication
, Journal Article
Renna, F; Calderbank, R; Carin, L; Rodrigues, MRD
Published in: 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
December 1, 2013
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. © 2013 IEEE.
Duke Scholars
Published In
2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
DOI
Publication Date
December 1, 2013
Start / End Page
628
Citation
APA
Chicago
ICMJE
MLA
NLM
Renna, F., Calderbank, R., Carin, L., & Rodrigues, M. R. D. (2013). Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, 628. https://doi.org/10.1109/GlobalSIP.2013.6736965
Renna, F., R. Calderbank, L. Carin, and M. R. D. Rodrigues. “Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view.” 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, December 1, 2013, 628. https://doi.org/10.1109/GlobalSIP.2013.6736965.
Renna F, Calderbank R, Carin L, Rodrigues MRD. Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings. 2013 Dec 1;628.
Renna, F., et al. “Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view.” 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings, Dec. 2013, p. 628. Scopus, doi:10.1109/GlobalSIP.2013.6736965.
Renna F, Calderbank R, Carin L, Rodrigues MRD. Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view. 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings. 2013 Dec 1;628.
Published In
2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
DOI
Publication Date
December 1, 2013
Start / End Page
628