Abstract

A task is randomly drawn from a finite set of tasks and is described using a fixed number of bits. All the tasks that share its description must be performed. Upper and lower bounds on the minimum ρρ-th moment of the number of performed tasks are derived. The key is an analog of the Kraft Inequality for partitions of finite sets. When a sequence of tasks is produced by a source of a given Rényi entropy rate of order 1/(1+ρ)1/(1+ρ) and nn tasks are jointly described using nRnR bits, it is shown that for RR larger than the Rényi entropy rate, the ρρ-th moment of the ratio of performed tasks to nn can be driven to one as nn tends to infinity, and that for RR less than the Rényi entropy rate it tends to infinity. This generalizes a recent result for IID sources by the same authors. A mismatched version of the direct part is also considered, where the code is designed according to the wrong law. The penalty incurred by the mismatch can be expressed in terms of a divergence measure that was shown by Sundaresan to play a similar role in the Massey-Arikan guessing problem.

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