标题： 高阶上下文变换 显示英文标题

标题： Higher Order Context Transformations

摘要： 上下文变换和广义上下文变换方法，我们最近引入的，能够通过交换二元组来减少零阶熵，因此，它们消除了输入消息中连续符号之间的互信息。 这些变换旨在用作零阶熵编码算法（如算术编码或霍夫曼编码）的预处理器，因为我们知道，尤其是算术编码可以实现接近香农熵大小的压缩率。 本文介绍了一种基于广义上下文变换概念的新算法，该算法允许对长于简单二元组的单词进行变换。 通过广义上下文变换的递归形式利用高阶上下文。 结果表明，变换后的数据的零阶熵显著下降，但另一方面，由单独变换描述带来的开销增加，并且已成为成功变换较小文件的限制因素。 显示英文摘要

摘要： The context transformation and generalized context transformation methods, we introduced recently, were able to reduce zero order entropy by exchanging digrams, and as a consequence, they were removing mutual information between consecutive symbols of the input message. These transformations were intended to be used as a preprocessor for zero-order entropy coding algorithms like Arithmetic or Huffman coding, since we know, that especially Arithmetic coding can achieve a compression rate almost of the size of Shannon's entropy. This paper introduces a novel algorithm based on the concept of generalized context transformation, that allows transformation of words longer than simple digrams. The higher order contexts are exploited using recursive form of a generalized context transformation. It is shown that the zero order entropy of transformed data drops significantly, but on the other hand, the overhead given by a description of individual transformations increases and it has become a limiting factor in a successful transformation of smaller files.