NDLI: A Universal Lossless Compressor with Side Information based on Context Tree Weighting

Content Provider	CiteSeerX
Abstract	Abstract — This paper proposes a new algorithm based on the Context-Tree Weighting method for universal compression of a finite-alphabet sequence x n 1 with side information y n 1 available to both the encoder and decoder. We prove that with probability one the compression ratio converges to the conditional entropy rate for jointly stationary ergodic sources. Experimental results with Markov chains and English texts show the effectiveness of the algorithm. I.
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Access Restriction	Open
Subject Keyword	Side Information Universal Lossless Compressor Context Tree Weighting Conditional Entropy Rate Context-tree Weighting Method Universal Compression English Text Finite-alphabet Sequence Stationary Ergodic Source Markov Chain Compression Ratio Converges
Content Type	Text
Resource Type	Article

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