Pareto-type finite-block optimality for source codes: a constrained Markov example

Abstract

We study a Pareto-type notion of finite-block optimality for injective source codes, where two codes are compared through the full sequence of expected block lengths. As a concrete and fully analyzable test case, we revisit the four-symbol constrained Markov source introduced by Dalai and Leonardi in their "meaningful example'' on constrained-source decodability. For each admissible nonempty string u=x1m ∈ A ⊂ X+, let K(u):=-2 P(X1m=u) denote its information cost. We construct a canonical injective binary mapping C:A \0,1\+ by ordering admissible strings by increasing K(u), then by length and lexicographic order, and assigning binary strings in shortlex order. For the length-n block X1n we prove E[|C(X1)|]=32, E[|C(X1n)|]<32\,n (n 2). Moreover, for every fixed 0<c<218π we have E[|C(X1n)|] 32\,n-c n for all sufficiently large n. Thus, for this source, the reversible Dalai-Leonardi code is not Pareto-optimal with respect to finite-block average length. The proof is based on an exact enumeration of admissible strings by information cost and on a shortlex gap identity implying that each cost class splits evenly between lengths K(u)-1 and K(u). The example is simple, but it already exhibits the kind of finite-block Pareto comparison that seems natural for injective source coding under source constraints.

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