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SUMMARY:Persistence of long-range-dependence under data compression - Anan
 tharam\, V (UC\, Berkeley)
DTSTART:20100323T093000Z
DTEND:20100323T103000Z
UID:TALK23846@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:One of the early motivations for current interest in the stoch
 astic networks community in the study of network models involving long-ran
 ge-dependent stochastic processes was the observation\, based on statistic
 al analysis of data\, that variable-bit-rate video traffic over networks a
 ppears to exhibit long-range-dependent behavior. Such traffic is typically
  placed on the network after data compression algorithms are used on an un
 derlying video source. It is natural to ask what role the data compression
  algorithm plays in the resulting long-range-dependent nature of the traff
 ic. Motivated by this question we study the entropy density of an underlyi
 ng long-range-dependent process as a stochastic process in its own right\,
  focusing on discrete time models. For classes of processes including rene
 wal processes we prove that long-range-dependence of the underlying proces
 s implies long-range-dependence of the entropy density process\, with the 
 same Hurst exponent. The underlying background in the data compression of 
 stochastic processes\, including the fundamental lemma of Barron relating 
 the entropy density to data compression\, and existing results for the sho
 rt-range-dependent case that have the same flavor as our results\, such as
  those due to Kontoyiannis\, will also be discussed in this talk. 
LOCATION:Seminar Room 1\, Newton Institute
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