Asymptotics of the quantization errors for some Markov-type measures with complete overlaps
Abstract
Let G be a directed graph with vertices 1,2,…, 2N. Let T=(Ti,j)(i,j)∈G be a family of contractive similitudes. For every 1≤ i≤ N, let i+:=i+N. For 1≤ i,j≤ N, we define Mi,j=\(i,j),(i,j+),(i+,j),(i+,j+)\. We assume that Ti,j=Ti,j for every (i,j)∈ Mi,j. Let K denote the Mauldin-Williams fractal determined by T. Let =(i)i=12N be a positive probability vector and P a row-stochastic matrix which serves as an incidence matrix for G. We denote by the Markov-type measure associated with and P. Let =\1,…,2N\ and G∞=\σ∈N:(σi,σi+1)∈G, \;i≥ 1\. Let π be the natural projection from G∞ to K and μ=π-1. We consider the following two cases: 1. G has two strongly connected components consisting of N vertices; 2. G is strongly connected. With some assumptions for G and T, for case 1, we determine the exact value sr of the quantization dimension Dr(μ) for μ and prove that the sr-dimensional lower quantization coefficient is always positive, but the upper one can be infinite; we establish a necessary and sufficient condition for the upper quantization coefficient for μ to be finite; for case 2, we determine Dr(μ) in terms of a pressure-like function and prove that Dr(μ)-dimensional upper and lower quantization coefficient are both positive and finite.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.