MMSE Estimation of Distributely Coded Correlated Gaussian Sources Using Random Projections

Author

Esnaola, Iñaki ; Garcia-Frias, Javier

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE

fYear

2008

Firstpage

1

Lastpage

5

Abstract

Recent developments in compressed sensing have shown that if a signal has a low Kolmogorov complexity, then it can be reconstructed from a certain number of random projections. We study the distributed coding of correlated Gaussian sources. Both intra- and inter-correlation models are considered in the source models. Decoding schemes in which it is possible to exploit the existing correlation between the signals of interest to significantly improve reconstruction performance are presented. This is done in a fashion resembling distributed coding of digital sources.

Keywords

Gaussian processes; correlation methods; decoding; least mean squares methods; random processes; sensor fusion; Kolmogorov complexity; MMSE estimation; compressed sensing; correlated Gaussian sources; decoding schemes; digital sources; distributed coding; intercorrelation models; intracorrelation models; random projections; reconstruction performance; Communication systems; Compressed sensing; Decoding; Distortion; Signal generators; Signal processing; Statistical distributions; Statistics; Stochastic processes; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE

Conference_Location

New Orleans, LO

ISSN

1930-529X

Print_ISBN

978-1-4244-2324-8

Type

conf

DOI

10.1109/GLOCOM.2008.ECP.673

Filename

4698448