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On Density and Sigma-Porosity in Some Families of Darboux Functions 一些达布函数族的密度和sigma -孔隙度
IF 0.2 Q4 MATHEMATICS Pub Date : 2022-06-01 DOI: 10.14321/realanalexch.47.1.1590599512
G. Ivanova, Irena Domnik
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引用次数: 0
A Brief Exposition of the Space of Relatively Bounded Nonlinear Operators 相对有界非线性算子空间的简要说明
IF 0.2 Q4 MATHEMATICS Pub Date : 2022-06-01 DOI: 10.14321/realanalexch.47.1.1610537860
P. Viswanathan
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引用次数: 0
Approximating the Decreasing Rearrangement 近似递减重排
IF 0.2 Q4 MATHEMATICS Pub Date : 2022-06-01 DOI: 10.14321/realanalexch.47.1.1596546460
Martin E. Price
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引用次数: 0
Comments on Charges on the Boolean Algebra of Regular Open Sets 正则开集布尔代数上电荷的注释
IF 0.2 Q4 MATHEMATICS Pub Date : 2022-06-01 DOI: 10.14321/realanalexch.47.1.1600145293
K. B. Bhaskara Rao
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引用次数: 0
On the Set of Points at which an Increasing Continuous Singular Function has a Nonzero Finite Derivative 关于递增连续奇异函数具有非零有限导数的点集
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-29 DOI: 10.14321/realanalexch.47.2.1638769133
Marta Kossaczká, L. Zajícek
Sanchez, Viader, Paradis and Carrillo (2016) proved that there exists an increasing continuous singular function $f$ on $[0,1]$ such that the set $A_f$ of points where $f$ has a nonzero finite derivative has Hausdorff dimension 1 in each subinterval of $[0,1]$. We prove a stronger (and optimal) result showing that a set $A_f$ as above can contain any prescribed $F_{sigma}$ null subset of $[0,1]$.
Sanchez,Viader,Paradis和Carrillo(2016)证明了在$[0,1]$上存在一个递增的连续奇异函数$f$,使得$f$具有非零有限导数的点的集合$A_f$在$[0.1]$的每个子区间中具有Hausdorff维数1。我们证明了一个更强(也是最优)的结果,表明如上所述的集合$a_f$可以包含$[0,1]$的任何规定的$f_{sigma}$null子集。
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引用次数: 0
ON FUNCTIONS DETERMINED BY DENSE SETS 关于稠密集确定的函数
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-01 DOI: 10.14321/REALANALEXCH.46.2.0423
Nicholas P. M. Kayban, Xianfu Wang
We show that a few basic classes of lower semicontinuous functions on ℝn are densely recoverable. Specifically, we show that the sum of a convex and a continuous function, the difference of two convex and lower semicontinuous functions, a K-increasing function (where K is a cone of nonempty interior), and differences of K-increasing functions are all functions uniquely determined by their values on a dense set in ℝn. Thus, sets of such functions of each type are densely recoverable sets. In general, the sum and difference of two densely recoverable sets of functions is shown to not be densely recoverable.
我们证明了上的几个下半连续函数的基本类ℝn是密集可采的。具体地说,我们证明了凸函数和连续函数的和、凸函数和下半连续函数的差、K增加函数(其中K是非空内部的锥)和K增加函数的差都是由它们在ℝn.因此,每种类型的这种函数的集合都是稠密可恢复集合。通常,两个稠密可恢复函数集的和和和差被证明是不稠密可恢复的。
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引用次数: 0
SOME REMARKS ON WASHEK PFEFFER'S CONTRIBUTIONS IN GENERAL TOPOLOGY 浅谈washek pfeffer在一般拓扑中的贡献
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-01 DOI: 10.14321/REALANALEXCH.46.2.0297
G. Gruenhage
Washek Pfeffer's contributions in general topology are discussed, especially his paper with van Douwen on $D$-spaces and his work with Prikry on small spaces.
讨论了Washek Pfeffer在一般拓扑中的贡献,特别是他与van Douwen关于$D$-空间的论文,以及他与Prikry关于小空间的工作。
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引用次数: 0
TOGO NISHIURA November 10, 1931 — February 12, 2021 TOGO NISHIURA November 10, 1931 — February 12, 2021
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-01 DOI: 10.14321/realanalexch.46.2.0301
P. Humke
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引用次数: 0
INEQUALITIES FOR WEIGHTED ARITHMETIC AND GEOMETRIC MEANS 加权算术不等式与几何平均
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-01 DOI: 10.14321/realanalexch.46.2.0359
H. Alzer
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引用次数: 0
OPTIMAL QUANTIZATION FOR MIXED DISTRIBUTIONS 混合分布的最优量化
IF 0.2 Q4 MATHEMATICS Pub Date : 2021-11-01 DOI: 10.14321/REALANALEXCH.46.2.0451
M. Roychowdhury
The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixed distributions are an exciting new area for optimal quantization. In this paper, we have determined the optimal sets of n-means, the nth quantization errors, and the quantization dimensions of different mixed distributions. Besides, we have discussed whether the quantization coefficients for the mixed distributions exist. The results in this paper will give a motivation and insight into more general problems in quantization for mixed distributions.
概率分布量化的基本目标是减少值的数量,这通常是不可计数的,将概率分布描述为某个有限集,从而通过离散分布近似连续概率分布。混合分布是优化量化的一个令人兴奋的新领域。在本文中,我们确定了不同混合分布的n均值、n量化误差和量化维数的最优集合。此外,我们还讨论了混合分布的量化系数是否存在。本文的结果将为混合分布量子化中更普遍的问题提供动力和见解。
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引用次数: 6
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Real Analysis Exchange
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