Mathematics > Functional Analysis
[Submitted on 15 Feb 2022 (v1), last revised 11 Jul 2023 (this version, v11)]
Title:Asymptotics of the quantization errors for some Markov-type measures with complete overlaps
View PDFAbstract:Let $\mathcal{G}$ be a directed graph with vertices $1,2,\ldots, 2N$. Let $\mathcal{T}=(T_{i,j})_{(i,j)\in\mathcal{G}}$ be a family of contractive similitudes. For every $1\leq i\leq N$, let $i^+:=i+N$. For $1\leq i,j\leq N$, we define $\mathcal{M}_{i,j}=\{(i,j),(i,j^+),(i^+,j),(i^+,j^+)\}\cap\mathcal{G}$. We assume that $T_{\widetilde{i},\widetilde{j}}=T_{i,j}$ for every $(\widetilde{i},\widetilde{j})\in \mathcal{M}_{i,j}$. Let $K$ denote the Mauldin-Williams fractal determined by $\mathcal{T}$. Let $\chi=(\chi_i)_{i=1}^{2N}$ be a positive probability vector and $P$ a row-stochastic matrix which serves as an incidence matrix for $\mathcal{G}$. We denote by $\nu$ the Markov-type measure associated with $\chi$ and $P$. Let $\Omega=\{1,\ldots,2N\}$ and $G_\infty=\{\sigma\in\Omega^{\mathbb{N}}:(\sigma_i,\sigma_{i+1})\in\mathcal{G}, \;i\geq 1\}$. Let $\pi$ be the natural projection from $G_\infty$ to $K$ and $\mu=\nu\circ\pi^{-1}$. We consider the following two cases: 1. $\mathcal{G}$ has two strongly connected components consisting of $N$ vertices; 2. $\mathcal{G}$ is strongly connected. With some assumptions for $\mathcal{G}$ and $\mathcal{T}$, for case 1, we determine the exact value $s_r$ of the quantization dimension $D_r(\mu)$ for $\mu$ and prove that the $s_r$-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 $\mu$ to be finite; for case 2, we determine $D_r(\mu)$ in terms of a pressure-like function and prove that $D_r(\mu)$-dimensional upper and lower quantization coefficient are both positive and finite.
Submission history
From: Sanguo Zhu [view email][v1] Tue, 15 Feb 2022 00:40:11 UTC (26 KB)
[v2] Tue, 22 Feb 2022 03:17:31 UTC (28 KB)
[v3] Sat, 18 Jun 2022 03:34:40 UTC (27 KB)
[v4] Sun, 26 Jun 2022 07:00:24 UTC (25 KB)
[v5] Fri, 1 Jul 2022 06:19:23 UTC (27 KB)
[v6] Fri, 8 Jul 2022 02:46:19 UTC (23 KB)
[v7] Thu, 14 Jul 2022 04:57:48 UTC (23 KB)
[v8] Fri, 22 Jul 2022 06:46:52 UTC (23 KB)
[v9] Fri, 29 Jul 2022 10:03:42 UTC (23 KB)
[v10] Sat, 27 Aug 2022 08:25:40 UTC (22 KB)
[v11] Tue, 11 Jul 2023 03:51:34 UTC (23 KB)
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