The universality and linearity of compression by substring enumeration

Danny Dubé, H. Yokoo
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引用次数: 14

Abstract

A new lossless data compression technique called compression by substring enumeration (CSE) has recently been introduced. Two conjectures have been stated in the original paper and they have not been proved there nor in subsequent papers on CSE. The first conjecture says that CSE is universal for Markovian sources, provided an appropriate predictor is devised. The second one says that CSE has a linear complexity both in time and in space. In this paper, we present an appropriate predictor and demonstrate that CSE indeed becomes universal for any order-k Markovian source. Finally, we prove that the compacted substring tree on which CSE's linear complexity depends effectively has linear size.
子串枚举压缩的通用性和线性性
一种新的无损数据压缩技术被称为子串枚举压缩(CSE)。两个猜想已经在原来的论文中陈述,他们没有被证明,也没有在随后的论文CSE。第一个猜想认为,如果设计出合适的预测器,CSE对于马尔可夫源是普遍的。第二种观点认为CSE在时间和空间上都具有线性复杂性。在本文中,我们提出了一个合适的预测器,并证明了CSE对于任何阶k马尔可夫源确实是普遍的。最后,我们证明了CSE的线性复杂度有效依赖的紧子串树具有线性大小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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