Are Guessing, Source Coding and Tasks Partitioning Birds of A Feather?

IF 2
M Ashok Kumar, Albert Sunny, Ashish Thakre, Ashisha Kumar, G Dinesh Manohar
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引用次数: 4

Abstract

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 in the IID-lossless case. 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. The unified framework further enables us to study a variant of Bunte-Lapidoth's tasks partitioning problem which is practically more appealing. In addition, this variant turns out to be a generalization of Arıkan'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.

Abstract Image

猜测、源代码编码和任务是一丘之貉吗?
本文建立了Campbell源编码、Arikan猜测、Huleihel等人的无记忆猜测和iid无损情况下的Bunte和Lapidoth任务划分问题这四个信息理论问题之间的密切关系。我们首先表明,上述问题是通过一般矩最小化问题在数学上相关的,该问题的最优解是根据Renyi熵给出的。然后,我们提出了这些问题的不匹配版本的一般框架,并利用该框架建立了所有的渐近结果。统一的框架进一步使我们能够研究一个更有吸引力的任务划分问题的变体。此外,这个变体原来是Arıkan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一个等价,在某种意义上,知道一个问题的渐近最优解有助于我们在所有其他问题中找到相同的渐近最优解。
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