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Sanguo Zhu

Publications and source records attributed to Sanguo Zhu.

At least 19 recordsLinked to original sources

Convergence order of the quantization error for self-affine measures on Lalley-Gatzouras carpets

Let $E$ be a Lalley-Gatzouras carpet determined by a set of contractive affine mappings $\{f_{ij}\}_{(i,j)\in G}$. We study the asymptotics of quantization error for the self-affine measures $\mu$ on $E$. We prove that the upper and lower quantization coefficient for $\mu$ are both bounded away from zero and infinity in the exact quantization dimension. This significantly generalizes the previous work concerning the quantization for self-affine measures on Bedford-McMullen carpets. The new ingredients lie in the method to bound the quantization error for $\mu$ from below and that to construct auxiliary measures by applying Prohorov's theorem.

math.CA

Asymptotic order of the quantization error for a class of self-similar measures with overlaps

Let $\{f_i\}_{i=1}^N$ be a set of equi-contractive similitudes on $\mathbb{R}^1$ satisfying the finite-type condition. We study the asymptotic quantization error for self-similar measures $μ$ associated with $\{f_i\}_{i=1}^N$ and a positive probability vector. With a verifiable assumption, we prove that the upper and lower quantization coefficient for $μ$ are both bounded away from zero and infinity. This can be regarded as an extension of Graf and Luschgy's result on self-similar measures with the open set condition. Our result is applicable to a significant class of self-similar measures with overlaps, including Erdös measure, the $3$-fold convolution of the classical Cantor measure and the self-similar measures on some $λ$-Cantor sets.

math.FA

Asymptotics of the quantization errors for some Markov-type measures with complete overlaps

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 $χ=(χ_i)_{i=1}^{2N}$ be a positive probability vector and $P$ a row-stochastic matrix which serves as an incidence matrix for $\mathcal{G}$. We denote by $ν$ the Markov-type measure associated with $χ$ and $P$. Let $Ω=\{1,\ldots,2N\}$ and $G_\infty=\{σ\inΩ^{\mathbb{N}}:(σ_i,σ_{i+1})\in\mathcal{G}, \;i\geq 1\}$. Let $π$ be the natural projection from $G_\infty$ to $K$ and $μ=ν\circπ^{-1}$. 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 $D_r(μ)$ for $μ$ 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 $μ$ to be finite; for case 2, we determine $D_r(μ)$ in terms of a pressure-like function and prove that $D_r(μ)$-dimensional upper and lower quantization coefficient are both positive and finite.

math.FA

Quantization dimensions of compactly supported probability measures via Rényi dimensions

We provide a complete picture of the upper quantization dimension in terms of the Rényi dimension by proving that the upper quantization dimension $\bar{D}_{r}(ν)$ of order $r>0$ for an arbitrary compactly supported Borel probability measure $ν$ is given by its Rényi dimension at the point $q_{r}$ where the $L^{q}$-spectrum of $ν$ and the line through the origin with slope $r$ intersect. In particular, this proves the continuity of $r\mapsto\bar{D}_{r}(ν)$ as conjectured by Lindsay (2001). This viewpoint also sheds new light on the connection of the quantization problem with other concepts from fractal geometry in that we obtain a one-to-one correspondence of the upper quantization dimension and the $L^{q}$-spectrum restricted to $\left(0,1\right)$. We give sufficient conditions in terms of the $L^{q}$-spectrum for the existence of the quantization dimension. In this way we show as a byproduct that the quantization dimension exists for every Gibbs measure with respect to a $\mathcal{C}^{1}$-self- conformal iterated function system on $\mathbb{R}^{d}$ without any assumption on the separation conditions as well as for inhomogeneous self-similar measures under the inhomogeneous open sets condition. Some known general bounds on the quantization dimension in terms of other fractal dimensions can readily be derived from our new approach, some can be improved.

math.PR

On the optimal Voronoi partitions for Ahlfors-David measures with respect to the geometric mean error

Let $μ$ be an Ahlfors-David probability measure on $\mathbb{R}^q$ with support $K$. For every $n\geq 1$, let $C_n(μ)$ denote the collection of all the $n$-optimal sets for $μ$ with respect to the geometric mean error. We prove that, there exist constant $d_1,d_2>0$, such that for each $n\geq 1$, every $α_n\in C_n(μ)$ and an arbitrary Voronoi partition $\{P_a(α_n)\}_{a\inα_n}$ with respect to $α_n$, we have \[ d_1n^{-1}\leq\min_{a\inα_n}μ(P_a(α_n))\leq\max_{a\inα_n}μ(P_a(α_n))\leq d_2n^{-1}. \] Moreover, we prove that each $P_a(α_n)$ contains a closed ball of radius $d_3|P_a(α_n)\cap K|$, where $d_3$ is a constant and $|B|$ denotes the diameter of a set $B\subset\mathbb{R}^q$. Some estimates for the measure and the geometrical size of the elements of a Voronoi partition with respect to an $n$-optimal set are established in a more general context.

math.PR

On the asymptotic quantization error for the doubling measures on Moran sets

We study the quantization errors for the doubling probability measures $μ$ which are supported on a class of Moran sets $E\subset\mathbb{R}^q$. For each $n\geq 1$, let $α_n$ be an arbitrary $n$-optimal set for $μ$ of order $r$ and $\{P_a(α_n)\}_{a\inα_n}$ an arbitrary Voronoi partition with respect to $α_n$. We denote by $I_a(α_n,μ)$ the integral $\int_{P_a(α_n)}d(x,a)^rdμ(x)$ and define \begin{eqnarray*} \underline{J}(α_n,μ):=\min\limits_{a\inα_n}I_a(α_n,μ),\; \overline{J}(α_n,μ):=\max\limits_{a\inα_n}I_a(α_n,μ). \end{eqnarray*} Let $e_{n,r}(μ)$ denote the $n$th quantization error for $μ$ of order $r$. Assuming a version of the open set condition for $E$, we prove that \[ \underline{J}(α_n,μ),\overline{J}(α_n,μ)\asymp\frac{1}{n}e_{n,r}^r(μ). \] This result shows that, for the doubling measures on Moran sets $E$, a weak version of Gersho's conjecture holds.

math.FA

Asymptotic order of the geometric mean error for self-affine measures on Bedford-McMullen carpets

Let $E$ be a Bedford-McMullen carpet associated with a set of affine mappings $\{f_{ij}\}_{(i,j)\in G}$ and let $μ$ be the self-affine measure associated with $\{f_{ij}\}_{(i,j)\in G}$ and a probability vector $(p_{ij})_{(i,j)\in G}$. We study the asymptotics of the geometric mean error in the quantization for $μ$. Let $s_0$ be the Hausdorff dimension for $μ$. Assuming a separation condition for $\{f_{ij}\}_{(i,j)\in G}$, we prove that the $n$th geometric error for $μ$ is of the same order as $n^{-1/s_0}$.

math.MG

Asymptotic local uniformity of the quantization error for Ahlfors-David probability measures

Let $μ$ be an Ahlfors-David probability measure on $\mathbb{R}^q$, namely, there exist some constants $s_0>0$ and $ε_0,C_1,C_2>0$ such that \[ C_1ε^{s_0}\leqμ(B(x,ε))\leq C_2ε^{s_0},\;ε\in(0,ε_0),\;x\in{\rm supp}(μ). \] For $n\geq 1$, let $α_n$ be an $n$-optimal set for $μ$ of order $r$ and $(P_a(α_n))_{a\inα_n}$ an arbitrary Voronoi partition with respect to $α_n$. The $n$th quantization error $e_{n,r}(μ)$ for $μ$ of order $r$ is given by $e^r_{n,r}(μ):=\int d(x,α_n)^rdμ(x)$. Write \[ I_a(α,μ):=\int_{P_a(α_n)}d(x,α_n)^rdμ(x),\;a\inα_n. \] We prove that, $\underline{J}(α_n,μ):=\min_{a\inα_n}I_a(α,μ)$, $\overline{J}(α_n,μ):=\max_{a\inα_n}I_a(α,μ)$ and the error difference $e^r_{n,r}(μ)-e^r_{n+1,r}(μ)$ are of the same order as $\frac{1}{n}e^r_{n,r}(μ)$. This, together with Graf and Luschgy's work, yields that all the above three quantities are of the same order as $n^{-(1+\frac{r}{s_0})}$.

math.MG

Asymptotic uniformity of the quantization error for Moran measures on $\mathbb{R}^1$

Let $E$ be a Moran set on $\mathbb{R}^1$ associated with a closed interval $J$ and two sequences $(n_k)_{k=1}^\infty$ and $(\mathcal{C}_k=(c_{k,j})_{j=1}^{n_k})_{k\geq1}$. Let $μ$ be the infinite product measure (Moran measure) on $E$ associated with a sequence $(\mathcal{P}_k)_{k\geq1}$ of positive probability vectors with $\mathcal{P}_k=(p_{k,j})_{j=1}^{n_k},k\geq 1$. We assume that \[ \inf_{k\geq1}\min_{1\leq j\leq n_k}c_{k,j}>0,\;\inf_{k\geq1}\min_{1\leq j\leq n_k}p_{k,j}>0. \] For every $n\geq 1$, let $α_n$ be an $n$ optimal set in the quantization for $μ$ of order $r\in(0,\infty)$ and $\{P_a(α_n)\}_{a\inα_n}$ an arbitrary Voronoi partition with respect to $α_n$. For every $a\inα_n$, we write $I_a(α,μ):=\int_{P_a(α_n)}d(x,α_n)^rdμ(x)$ and \[ \underline{J}(α_n,μ):=\min_{a\inα_n}I_a(α,μ),\; \overline{J}(α_n,μ):=\max_{a\inα_n}I_a(α,μ). \] We show that $\underline{J}(α_n,μ),\overline{J}(α_n,μ)$ and $e^r_{n,r}(μ)-e^r_{n+1,r}(μ)$ are of the same order as $\frac{1}{n}e^r_{n,r}(μ)$, where $e^r_{n,r}(μ):=\int d(x,α_n)^rdμ(x)$ is the $n$th quantization error for $μ$ of order $r$. In particular, for the class of Moran measures on $\mathbb{R}^1$, our result shows that a weaker version of Gersho's conjecture holds.

math.FA

Exact convergence order of the $L_r$-quantization error for Markov-type measures

Let $E$ be a graph-directed set associated with a di-graph $G$. Let $μ$ be a Markov-type measure on $E$. Assuming a separation condition for $E$, we determine the exact convergence order of the $L_r$-quantization error for $μ$. This result provides us with accurate information on the asymptotics of the quantization error, especially when the quantization coefficient is infinite.

math.MG

A note on the quantization error for in-homogeneous self-similar measures

We further study the asymptotics of quantization errors for two classes of in-homogeneous self-similar measures $μ$. We give a new sufficient condition for the upper quantization coefficient for $μ$ to be finite. This, together with our previous work, leads to a necessary and sufficient condition for the upper and lower quantization coefficient of $μ$ to be both positive and finite. Furthermore, we determine (estimate) the convergence order of the quantization error in case that the quantization coefficient is infinite.

math.MG

Asymptotic order of the quantization errors for self-affine measures on Bedford-McMullen carpets

Let $E$ be a Bedford-McMullen carpet determined by a set of affine mappings $(f_{ij})_{(i,j)\in G}$ and $μ$ a self-affine measure on $E$ associated with a probability vector $(p_{ij})_{(i,j)\in G}$. We prove that, for every $r\in(0,\infty)$, the upper and lower quantization coefficient are always positive and finite in its exact quantization dimension $s_r$. As a consequence, the $k$th quantization error for $μ$ of order $r$ is of the same order as $k^{-\frac{1}{s_r}}$. In sharp contrast to the Hausdorff measure for Bedford-McMullen carpets, our result is independent of the horizontal fibres of the carpets.

math.MG

Some recent developments in quantization of fractal measures

We give an overview on the quantization problem for fractal measures, including some related results and methods which have been developed in the last decades. Based on the work of Graf and Luschgy, we propose a three-step procedure to estimate the quantization errors. We survey some recent progress, which makes use of this procedure, including the quantization for self-affine measures, Markov-type measures on graph-directed fractals, and product measures on multiscale Moran sets. Several open problems are mentioned.

math.PR

Convergence order of the geometric mean errors for Markov-type measures

We study the quantization problem with respect to the geometric mean error for Markov-type measures $μ$ on a class of fractal sets. Assuming the irreducibility of the corresponding transition matrix $P$, we determine the exact convergence order of the geometric mean errors of $μ$. In particular, we show that, the quantization dimension of order zero is independent of the initial probability vector when $P$ is irreducible, while this is not true if $P$ is reducible.

math.MG

Asymptotics of the geometric mean error for in-homogeneous self-similar measures

Let $(f_i)_{i=1}^N$ be a family of contractive similitudes on $\mathbb{R}^q$ satisfying the open set condition. Let $(p_i)_{i=0}^N$ be a probability vector with $p_i>0$ for all $i=0,1,\ldots,N$. We study the asymptotic geometric mean errors $e_{n,0}(μ),n\geq 1$, in the quantization for the in-homogeneous self-similar measure $μ$ associated with the condensation system $((f_i)_{i=1}^N,(p_i)_{i=0}^N,ν)$. We focus on the following two independent cases: (I) $ν$ is a self-similar measure on $\mathbb{R}^q$ associated with $(f_i)_{i=1}^N$; (II) $ν$ is a self-similar measure associated with another family of contractive similitudes $(g_i)_{i=1}^M$ on $\mathbb{R}^q$ satisfying the open set condition and $((f_i)_{i=1}^N,(p_i)_{i=0}^N,ν)$ satisfies a version of in-homogeneous open set condition. We show that, in both cases, the quantization dimension $D_0(μ)$ of $μ$ of order zero exists and agrees with that of $ν$, which is independent of the probability vector $(p_i)_{i=0}^N$. We determine the convergence order of $(e_{n,0}(μ))_{n=1}^\infty$; namely, for $D_0(μ)=:d_0$, there exists a constant $D>0$, such that \[ D^{-1}n^{-\frac{1}{d_0}}\leq e_{n,0}(μ)\leq D n^{-\frac{1}{d_0}}, n\geq 1. \]

math.DS

Asymptotic quantization errors for in-homogeneous self-similar measures supported on self-similar sets

We study the quantization for a class of in-homogeneous self-similar measures $μ$ supported on self-similar sets. Assuming the open set condition for the corresponding iterated function system, we prove the existence of the quantization dimension for $μ$ of order $r\in(0,\infty)$ and determine its exact value $ξ_r$. Furthermore, we show that, the $ξ_r$-dimensional lower quantization coefficient for $μ$ is always positive and the upper one can be infinite. We also give a sufficient condition to ensure the finiteness of the upper quantization coefficient.

math.MG

The quantization for in-homogeneous self-similar measures with in-homogeneous open set condition

Let $(g_i)_{i=1}^M$ be a family of contractive similitudes satisfying the open set condition. Let $ν$ be a self-similar measure associated with $(g_i)_{i=1}^M$. We study the quantization problem for the in-homogeneous self-similar measure $μ$ associated with a condensation system $((f_i)_{i=1}^N,(p_i)_{i=0}^N,ν)$. Assuming a version of in-homogeneous open set condition for this system, we prove the existence of the quantization dimension for $μ$ of order $r\in(0,\infty)$ and determine its exact value $ξ_r$. We give sufficient conditions for the $ξ_r$-dimensional upper and lower quantization coefficient to be positive or finite.

math.FA

The quantization for Markov-type measures on a class of ratio-specified graph directed fractals

We study the asymptotic quantization error of order $r$ for Markov-type measures $μ$ on a class of ratio-specified graph directed fractals. We show that the quantization dimension of $μ$ exists and determine its exact value $s_{r}$ in terms of spectral radius of a related matrix. We prove that the $s_{r}$-dimensional lower quantization coefficient of $μ$ is always positive. Moreover, inspired by Mauldin-Williams's work on the Hausdorff measure of graph directed fractals, we establish a necessary and sufficient condition for the $s_{r}$-dimensional upper quantization coefficient of $μ$ to be finite.

math.PR