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Alphabet Sizes of Auxiliary Random Variables in Canonical Inner Bounds

机译:典型内界中辅助随机变量的字母表大小

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Recently, we proposed canonical inner bounds for a broad class of multiterminal source coding problems, subsuming an array of known results. Computation of those bounds assumes importance in view of open tightness questions, as well as their role as benchmarks, and in other contexts. In this backdrop, as computational algorithms depend exponentially on alphabet sizes of auxiliary random variables, estimating their sizes remains an important task. In existing literature, each auxiliary alphabet size is bounded within a positive integer constant of the corresponding source alphabet size. In a significant improvement, we give a tight bound, by showing that this constant integer can in fact be set to zero.
机译:最近,我们提出了广泛的多阶段源编码问题的规范内界,归入了一系列已知结果。考虑到开放紧密性问题以及它们作为基准的角色以及在其他情况下,计算这些界限的计算假定重要性。在此背景中,随着计算算法以辅助随机变量的字母大小指数呈指数级,估计它们的尺寸仍然是一个重要任务。在现有文献中,每个辅助字母表大小在相应源字母大小的正整数常数内界定。在显着的改进中,我们提供了紧密的绑定,通过表示实际上可以设置为零。

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