Lossy computing of correlated sources with fractional sampling

Xi Liu, Osvaldo Simeone, Elza Erkip

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. For both Gaussian and binary sources, the distortion-rate function, or rate-distortion function, is characterized for selected functions and with quadratic and Hamming distortion metrics, respectively. Based on these results, for both examples, the optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source correlation and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy.

Original languageEnglish (US)
Title of host publication2012 IEEE Information Theory Workshop, ITW 2012
Pages232-236
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE Information Theory Workshop, ITW 2012 - Lausanne, Switzerland
Duration: Sep 3 2012Sep 7 2012

Publication series

Name2012 IEEE Information Theory Workshop, ITW 2012

Other

Other2012 IEEE Information Theory Workshop, ITW 2012
CountrySwitzerland
CityLausanne
Period9/3/129/7/12

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Liu, X., Simeone, O., & Erkip, E. (2012). Lossy computing of correlated sources with fractional sampling. In 2012 IEEE Information Theory Workshop, ITW 2012 (pp. 232-236). [6404665] (2012 IEEE Information Theory Workshop, ITW 2012). https://doi.org/10.1109/ITW.2012.6404665