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• W1639709558 abstract "This paper examines information-theoretic questions regarding the difficulty of compressing data versus the difficulty of decompressing data and the role that information loss plays in this interaction. Finite-state compression and decompression are shown to be of equivalent difficulty, even when the decompressors are allowed to be lossy.Inspired by Kolmogorov complexity, this paper defines the optimal *decompression *ratio achievable on an infinite sequence by finite-state decompressors (that is, finite-state transducers outputting the sequence in question). It is shown that the optimal compression ratio achievable on a sequence S by any *information lossless* finite state compressor, known as the finite-state dimension of S, is equal to the optimal decompression ratio achievable on S by any finite-state decompressor. This result implies a new decompression characterization of finite-state dimension in terms of lossy finite-state transducers." @default.
• W1639709558 created "2016-06-24" @default.
• W1639709558 creator A5061641572 @default.
• W1639709558 creator A5072272219 @default.
• W1639709558 date "2006-09-18" @default.
• W1639709558 modified "2023-09-27" @default.
• W1639709558 title "Finite-State Dimension and Lossy Decompressors" @default.
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