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
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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 -