On sliding-window universal data compression with limited memory
Y Hershkovits, J Ziv - IEEE Transactions on Information Theory, 1998 - ieeexplore.ieee.org
Nonasymptotic coding and converse theorems are derived for universal data compression
algorithms in cases where the training sequence (" history") that is available to the encoder
consists of the most recent segment of the input data string that has been processed, but is
not large enough so as to yield the ultimate compression, namely, the entropy of the source.
algorithms in cases where the training sequence (" history") that is available to the encoder
consists of the most recent segment of the input data string that has been processed, but is
not large enough so as to yield the ultimate compression, namely, the entropy of the source.
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