Compression based on asymmetric numeral systems (ANS) combines high encoding and decoding speeds with a compression ratio close to Shannon entropy, while forward modeling of the information source makes it possible to obtain an estimated compressed message size that is less than the entropy. This paper proposes combining these modeling and adaptive coding methods. In addition to ensuring high data processing speeds and compression ratios, this approach enables one to implement the adaptive ANS, which has long remained an important scientific and practical problem.

翻译：基于非对称数系（ANS）的压缩方法结合了高编码与解码速度，其压缩比接近香农熵，而对信息源的前向建模能使得估算的压缩消息大小低于熵值。本文提出将这些建模方法与自适应编码技术相结合。该方法除了确保高数据处理速度与压缩比外，还使得实现长期以来作为重要科学与实践问题的自适应ANS成为可能。