关于f-可分离失真测度的编码定理。
A Coding Theorem for f-Separable Distortion Measures.
作者信息
Shkel Yanina, Verdú Sergio
机构信息
Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA.
出版信息
Entropy (Basel). 2018 Feb 8;20(2):111. doi: 10.3390/e20020111.
In this work we relax the usual separability assumption made in rate-distortion literature and propose f -separable distortion measures, which are well suited to model non-linear penalties. The main insight behind f -separable distortion measures is to define an -letter distortion measure to be an f -mean of single-letter distortions. We prove a rate-distortion coding theorem for stationary ergodic sources with f -separable distortion measures, and provide some illustrative examples of the resulting rate-distortion functions. Finally, we discuss connections between f -separable distortion measures, and the subadditive distortion measure previously proposed in literature.
在这项工作中，我们放宽了率失真文献中通常所做的可分性假设，并提出了f -可分失真度量，它非常适合于对非线性惩罚进行建模。f -可分失真度量背后的主要见解是将一个n字母失真度量定义为单字母失真的f -均值。我们证明了具有f -可分失真度量的平稳遍历源的率失真编码定理，并给出了一些由此产生的率失真函数的示例。最后，我们讨论了f -可分失真度量与文献中先前提出的次可加失真度量之间的联系。
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