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Alphabet sizes of auxiliary random variables in canonical inner bounds

机译:规范内界中辅助随机变量的字母大小

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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,我们提出了一系列广泛的多终端源编码问题的规范内边界,并包含了一系列已知结果。考虑到开放性紧密度问题,它们作为基准的作用以及在其他情况下,计算这些界限至关重要。在这种情况下,由于计算算法以指数方式取决于辅助随机变量的字母大小,因此估计其大小仍然是一项重要的任务。在现有文献中,每个辅助字母的大小都限制在相应源字母大小的正整数常数内。通过显着改进,我们证明了这个常数整数实际上可以设置为零,从而给出了一个严格的界限。

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