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Universal data compression algorithms by using normal tree models

机译:通过使用普通树模型来实现通用数据压缩算法

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Universal data compression algorithms are the algorithms by which source data can be coded without a priori knowledge of statistics of a source. This paper describes two techniques for constructing and updating normal trees-adding and discarding. Two universal data compression algorithms and their tree source models are proposed and their implementations are suggested. These algorithms are evaluated by three parameters-the normalized average code lengths, required memory spaces, and encoding complexities.
机译:通用数据压缩算法是可以在没有先验的源统计知识的情况下对源数据进行编码的算法。本文介绍了两种构建和更新正常树木添加和丢弃的技术。提出了两个通用数据压缩算法及其树源模型,并提出了其实现。这些算法由三个参数评估 - 标准化的平均代码长度,所需的存储空间和编码复杂性。

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