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On fixed-database universal data compression with limited memory

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2 Author(s)
Y. Hershkovits ; Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel ; J. Ziv

The amount of fixed side information required for lossless data compression is discussed. Nonasymptotic coding and converse theorems are derived for data-compression algorithms with fixed statistical side information (“training sequence”) that is not large enough so as to yield the ultimate compression, namely, the entropy of the source

Published in:

IEEE Transactions on Information Theory  (Volume:43 ,  Issue: 6 )