TY - GEN

T1 - Lossy computing of correlated sources with fractional sampling

AU - Liu, Xi

AU - Simeone, Osvaldo

AU - Erkip, Elza

N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84873113981&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84873113981&partnerID=8YFLogxK

U2 - 10.1109/ITW.2012.6404665

DO - 10.1109/ITW.2012.6404665

M3 - Conference contribution

AN - SCOPUS:84873113981

SN - 9781467302234

T3 - 2012 IEEE Information Theory Workshop, ITW 2012

SP - 232

EP - 236

BT - 2012 IEEE Information Theory Workshop, ITW 2012

T2 - 2012 IEEE Information Theory Workshop, ITW 2012

Y2 - 3 September 2012 through 7 September 2012

ER -