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An information theoretic model for adaptive lossy compression

机译:一种自适应损耗压缩的信息理论模型

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We investigate the underlying mechanism of universal sequential, fixed distortion, lossy source coding algorithms, through the "eyes" of a random code. We model the adaptive codebook as a "mixed type" random code whose codeword type distribution evolves with time while its dimension goes to infinity. The evolution law in our model has a structure of a tree; a type inherits its frequency in the code from its parent-types matching probabilities. We find that this mechanism naturally selects the "good" codeword types for compressing the (unknown) source. As a consequence, the code becomes optimal for the source, and approaches the rate-distortion function as the time, and hence the dimension, go to infinity. Beyond its analytical interest, this model also provides guidelines for developing lossy string matching (Lempel-Ziv-like) algorithms.
机译:我们调查通用顺序,固定失真,有损源码编码算法的潜在机制,通过随机代码的“眼睛”。我们将自适应码本模拟为“混合类型”随机代码,其码字类型分发随时间演变的时间,而其尺寸变为无穷大。我们模型中的进化法具有树的结构;一种类型从其父级匹配概率继承其代码中的频率。我们发现该机制自然地选择了用于压缩(未知)源的“良好”码字类型。结果,代码对源变为最佳,并且接近速率失真函数,因此尺寸,转到无限远。除了其分析兴趣之外,该模型还提供了开发有损串匹配(LEMPEL-ZIV样)算法的指导。

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