Rate-distortion theory for Gaussian multiterminal source coding systems with several side informations at the decoder

In this paper, we consider the separate coding problem for L+1 correlated Gaussian memoryless sources. We deal with the case where L sources work as partial side information at the decoder for the reconstruction of the remaining source. The determination problem of the rate-distortion region for thi...

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Vydáno v:IEEE transactions on information theory Ročník 51; číslo 7; s. 2577 - 2593
Hlavní autor: Oohama, Y.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.07.2005
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Additive white noise
Additives
Africa
Applied sciences
CEO problem
Codes
Coding
Coding, codes
Communication systems
Communications systems
Conferences
Correlation
Decoders
Decoding
Error probability
Exact sciences and technology
Gaussian
Information theory
Information, signal and communications theory
many-help-one prob- lem
multiterminal source coding
Noise
Normal distribution
Random variables
Rate-distortion
rate-distortion region
Reconstruction
Signal and communications theory
Source coding
Telecommunications and information theory
AWGN
Source coding
many-help-one problem
multiterminal source coding
Gaussian signal
rate-distortion region
Rate distortion theory
CEO problem
Gaussian
ISSN:0018-9448, 1557-9654
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Popis
Shrnutí:In this paper, we consider the separate coding problem for L+1 correlated Gaussian memoryless sources. We deal with the case where L sources work as partial side information at the decoder for the reconstruction of the remaining source. The determination problem of the rate-distortion region for this system is the so-called many-help-one problem and it has been known as a highly challenging problem for almost 20 years. In this paper, we give a partial solution to this problem. We determine the rate-distortion region in the case where the L sources working as partial side information are conditionally independent if the remaining source we wish to reconstruct is given. The additive white Gaussian noise CEO problem is a special case of this. We also discuss the relation of the result previous results of ours
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2005.850110