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Universal Simulation with Fidelity Criteria
Merhav, Neri; Weinberger, Marcelo J.
HPL2007148
Keyword(s): universal simulation; distance measures; generalized divergence
Abstract: We consider the problem of universal simulation of a memoryless source (with some partial extensions to Markov sources), based on a training sequence emitted from the source. The objective is to maximize the conditional entropy of the simulated sequence given the training sequence, subject to a certain distance constraint between the probability distribution of the output sequence and the probability distribution of the input, training sequence. We derive, for several distance criteria, singleletter expressions for the maximum attainable conditional entropy as well as corresponding universal simulation schemes that asymptotically attain these maxima.
11 Pages
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