论文标题
是否猜测，来源编码和将羽毛鸟类分区的任务？
Are Guessing, Source Coding, and Tasks Partitioning Birds of a Feather?
论文作者
论文摘要
本文在四个信息理论问题（即坎贝尔源编码，阿里坎猜测）中建立了密切的关系，Huleihel等人。无内存的猜测以及bunte和拉皮斯任务分区问题。我们首先表明，上述问题是通过一般时刻最小化问题在数学上相关的，该问题的最佳解决方案是根据Renyi熵给出的。然后，我们为这些问题的不匹配版本提出了一个通用框架，并使用此框架建立了所有渐近结果。此外，我们研究了一个有序的任务分区问题，该任务被证明是阿里肯猜测问题的概括。最后，在这个一般框架的帮助下，我们在所有这些问题之间建立了等效性，从某种意义上说，在一个问题中了解一个渐近最佳的解决方案有助于我们在所有其他问题中找到相同的问题。
This paper establishes a close relationship among the four information theoretic problems, namely Campbell source coding, Arikan guessing, Huleihel et al. memoryless guessing and Bunte and Lapidoth tasks partitioning problems. We first show that the aforementioned problems are mathematically related via a general moment minimization problem whose optimum solution is given in terms of Renyi entropy. We then propose a general framework for the mismatched version of these problems and establish all the asymptotic results using this framework. Further, we study an ordered tasks partitioning problem that turns out to be a generalisation of Arikan's guessing problem. Finally, with the help of this general framework, we establish an equivalence among all these problems, in the sense that, knowing an asymptotically optimal solution in one problem helps us find the same in all other problems.
