WE1.R4.4

Implicit and Explicit Formulas of the Joint RDF for a Tuple of Multivariate Gaussian Sources with Individual Square-Error Distortions

Evagoras Stylianou, Technical University of Munich, Germany; Charalambos D. Charalambous, Themistoklis Charalambous, University of Cyprus, Cyprus
Session:
Multi Terminal Source Coding
Track:
10: Source Coding and Data Compression
Location:
Omikron II
Presentation Time:
Wed, 10 Jul, 10:50 - 11:10
Session Chair:
Stark Draper, University of Toronto
Abstract
This paper analyzes the joint Rate Distortion Function (RDF) of correlated multivariate Gaussian sources with individual square-error distortions. Leveraging Hotelling's canonical variable form (CVF), presented is a closed-form characterization of the joint RDF, that involves {a system of nonlinear equations. Furthermore, for the special case of symmetric distortions (i.e., equal distortions), the joint RDF is explicitly expressed in terms of} two water-filling variables. The results greatly improve our understanding and advance the development of closed-form solutions of the joint RDF for multivariate Gaussian sources with individual square-error distortions.
Session WE1.R4
WE1.R4.1: Common Function Reconstruction with Information Swapping Terminals
Tharindu Adikari, Stark Draper, University of Toronto, Canada
WE1.R4.2: Distributed Source Coding Using Constrained-Random-Number Generators
Jun Muramatsu, Nippon Telegraph and Telephone Corporation, Japan
WE1.R4.3: On Channel Simulation with Causal Rejection Samplers
Daniel Goc, Gergely Flamich, University of Cambridge, United Kingdom
WE1.R4.4: Implicit and Explicit Formulas of the Joint RDF for a Tuple of Multivariate Gaussian Sources with Individual Square-Error Distortions
Evagoras Stylianou, Technical University of Munich, Germany; Charalambos D. Charalambous, Themistoklis Charalambous, University of Cyprus, Cyprus
Resources
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