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RESEARCHCONTRlBllTlONS Algorithms and Data Structures Daniel Sleator Editor Data Compression with Finite Windows EDWARDR. FIALA and DANIEL H. GREENE ABSTRACT: Sevt,ral methods are presented for adaptive, invertible data complression in the style of Lempel s and Ziv s first textual substitution proposal. For the first two methods, the article describes modifications of McCreight s suffix tree data strut ture that support cyclic maintenance of a window on the most recent source characters. A percolating update i:; used to keep node positions within the window, and the updating process is shown to have constant amortized cost. Other methods explore the tradeoffs between compression time, expansion time, data structure size, and amount of compression achieved. The article includes a graph-theoretic analysis of the compression penalty incurred by our codeword selt ction policy in comparison with an optimal policy, and It includes empirical studies of the performance of various adaptive compressors from the literature. 1. INTRODUCTION Compression is the coding of data to minimize its representation. In this al,ticle, we are concerned with fast, one-pass, adaptive, invertible (or lossless) methods of digital compression which have reasonable memory requirements. SUCK.methods can be used, for example, to reduce the storal;e requirements for files,
Communications of the ACM – Association for Computing Machinery
Published: Apr 1, 1989
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