Abstract
In this paper we analyze the joint rate distortion function (RDF), for a tuple of correlated sources taking values in abstract alphabet spaces (i.e., continuous) subject to two individual distortion criteria. First, we derive structural properties of the realizations of the reproduction Random Variables (RVs), which induce the corresponding optimal test channel distributions of the joint RDF. Second, we consider a tuple of correlated multivariate jointly Gaussian RVs, X_{1}:\Omega\rightarrow \mathbb{R}^{p_{1, X_{2}:\Omega\rightarrow \mathbb{R}^{p_{2 with two square-error fidelity criteria, and we derive additional structural properties of the optimal realizations, and use these to characterize the RDF as a convex optimization problem with respect to the parameters of the realizations. We show that the computation of the joint RDF can be performed by semidefinite programming. Further, we derive closed-form expressions of the joint RDF, such that Gray's [1] lower bounds hold with equality, and verify their consistency with the semidefinite programming computations.
Original language | English |
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Title of host publication | Proceedings of IEEE International Symposium on Information Theory, ISIT 2021 |
Publisher | IEEE |
Pages | 2167-2172 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-5386-8209-8 |
DOIs | |
Publication status | Published - 1 Sept 2021 |
MoE publication type | A4 Conference publication |
Event | IEEE International Symposium on Information Theory - Virtual, online, Melbourne, Australia Duration: 12 Jul 2021 → 20 Jul 2021 https://2021.ieee-isit.org/ |
Conference
Conference | IEEE International Symposium on Information Theory |
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Abbreviated title | ISIT |
Country/Territory | Australia |
City | Melbourne |
Period | 12/07/2021 → 20/07/2021 |
Internet address |