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Arithmetic Coding As A Non-linear Dynamical System

机译:算术编码作为非线性动力系统

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摘要

In order to perform source coding (data compression), we treat messages emitted by independent and identically distributed sources as imprecise measurements (symbolic sequence) of a chaotic, ergodic, Lebesgue measure preserving, nonlinear dynamical system known as Generalized Luroth Series (GLS). GLS achieves Shannon's entropy bound and turns out to be a generalization of arithmetic coding, a popular source coding algorithm, used in international compression standards such as JPEG2000 and H.264. We further generalize GLS to piecewise non-linear maps (Skewed-nGLS). We motivate the use of Skewed-nGLS as a framework for joint source coding and encryption.
机译:为了执行源代码编码(数据压缩),我们将由独立且分布均匀的源发出的消息视为被称为广义Luroth系列(GLS)的混沌,遍历,Lebesgue度量保留的非线性动力学系统的不精确度量(符号序列)。 GLS达到了Shannon的熵界,并证明它是算术编码的一种概括,一种流行的源编码算法,用于JPEG2000和H.264等国际压缩标准。我们进一步将GLS推广到分段非线性映射(Skewed-nGLS)。我们鼓励将Skewed-nGLS用作联合源编码和加密的框架。

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