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Computable type and computably categorical spaces 可计算类型空间和可计算分类空间
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2026-02-03 DOI: 10.1016/j.jco.2026.102026
Zvonko Iljazović , Patrik Vasung
We examine effective separating sequences on a metric space and, in particular, conditions under which on a metric space every two such sequences are equivalent up to an isometry. Such a metric space is called computably categorical. We prove that an effectively compact metric space (X,d) is computably categorical if the space Iso(X,d) of all isometries of (X,d) has computable type (which in particular holds if Iso(X,d) is a manifold). Using this, we prove that each effectively compact subspace of Euclidean space is computably categorical.
我们研究了度量空间上的有效分离序列,特别是在度量空间上每两个这样的序列等价于等距的条件。这样的度量空间称为可计算范畴空间。证明了如果(X,d)的所有等距空间Iso(X,d)具有可计算类型(特别是当Iso(X,d)是流形时),则有效紧化度量空间(X,d)是可计算范畴的。由此证明了欧几里得空间的每个有效紧化子空间都是可计算的范畴空间。
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引用次数: 0
Weighted approximate sampling recovery and integration based on B-spline interpolation and quasi-interpolation 基于b样条插值和拟插值的加权近似采样恢复与积分
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2026-01-08 DOI: 10.1016/j.jco.2026.102016
Dinh Dũng
We propose novel methods for approximate sampling recovery and integration of functions in the Freud-weighted Sobolev space Wp,wr(R). The approximation error of sampling recovery is measured in the norm of the Freud-weighted Lebesgue space Lq,w(R). Namely, we construct equidistant, compact-supported B-spline quasi-interpolation and interpolation sampling algorithms Qρ,m and Pρ,m which are asymptotically optimal in terms of the sampling n-widths ϱn(Wp,wr(R),Lq,w(R)) for every pair p,q[1,], and prove the exact convergence rate of these sampling n-widths, where Wp,wr(R) denotes the unit ball in Wp,wr(R). The algorithms Qρ,m and Pρ,m are based on truncated scaled B-spline quasi-interpolation and interpolation, respectively. We also prove the asymptotical optimality and exact convergence rate of the equidistant quadratures generated from Qρ,m and Pρ,m, for Freud-weighted numerical integration of functions in Wp,wr(R).
我们提出了一种新的方法来近似采样恢复和积分函数在弗洛伊德加权Sobolev空间Wp,wr(R)。采样恢复的近似误差在弗洛伊德加权勒贝格空间的范数Lq,w(R)中测量。即,对每一对p,q∈[1,∞],我们构造了对采样n-宽度ϱn(Wp,wr(R),Lq,w(R))渐近最优的等距紧支持b样条拟插值和插值采样算法Qρ,m和p, m,并证明了这些采样n-宽度的精确收敛速率,其中Wp,wr(R)表示Wp,wr(R)中的单位球。算法Qρ,m和Pρ,m分别基于截断尺度b样条准插值和插值。对于函数在Wp,wr(R)中的弗洛伊德加权数值积分,我们也证明了由Qρ,m和Pρ,m生成的等距正交的渐近最优性和精确收敛率。
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引用次数: 0
Average case tractability of additive random fields with Korobov kernels 具有Korobov核的可加随机场的平均情况可追溯性
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2026-01-06 DOI: 10.1016/j.jco.2025.102015
Jia Chen , Heping Wang
We investigate average case tractability of approximation of additive random fields with marginal random processes corresponding to the Korobov kernels for the non-homogeneous case. We use the absolute error criterion (ABS) or the normalized error criterion (NOR). We show that the approximation problem is always polynomially tractable for ABS or NOR, and give sufficient and necessary conditions for strong polynomial tractability for ABS or NOR.
研究了非齐次情况下具有Korobov核的边缘随机过程的加性随机场的逼近的平均情况可跟踪性。我们使用绝对误差准则(ABS)或归一化误差准则(NOR)。我们证明了ABS或NOR的近似问题总是多项式可处理的,并给出了ABS或NOR的强多项式可处理的充要条件。
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引用次数: 0
Landweber iteration for inverse problems using multiple repeated measurements data in Banach spaces Banach空间中多重重复测量数据反演问题的Landweber迭代
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-12-22 DOI: 10.1016/j.jco.2025.102014
Yuxin Xia , Wei Wang , Yong Chen
In this work we consider Landweber iteration for solving generic linear inverse problems in the Banach spaces setting. Landweber iteration, along with its variants, is widely recognized as one of the most prominent iterative regularization methods due to its ease of implementation. Unlike classical theoretical analyses, this work considers the absence of noise level information, making it more relevant to real-world applications. We assume that multiple repeated independent identically distributed unbiased measurements of the exact data are available. The average of these repeated measurements is then utilized to update the iterative process. Under a statistical variant of the discrepancy principle, we establish rigorous regularizing property in the sense of expectation. Furthermore, a series of numerical experiments are conducted to evaluate and validate the performance of the approach.
在这项工作中,我们考虑Landweber迭代求解Banach空间设置下的一般线性逆问题。由于易于实现,Landweber迭代及其变体被广泛认为是最突出的迭代正则化方法之一。与经典理论分析不同,这项工作考虑了噪声水平信息的缺失,使其与现实世界的应用更相关。我们假设有多个重复的、独立的、同分布的、无偏的精确数据测量。然后利用这些重复测量的平均值来更新迭代过程。在差异原理的一个统计变体下,我们建立了期望意义上的严格正则化性质。此外,通过一系列数值实验对该方法的性能进行了评价和验证。
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引用次数: 0
Regularization operators for identifying the unknown source in the time-fractional convection-diffusion-reaction equation 用于识别时间分数对流-扩散-反应方程中未知源的正则化算子
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-12-11 DOI: 10.1016/j.jco.2025.102013
Guillermo Federico Umbricht , Diana Rubio
This article presents a mathematical study of the problem of identifying a time-dependent source term in transport processes described by a time-fractional parabolic equation, based on noisy time-dependent measurements taken at an arbitrary position. The problem is analytically solved using Fourier techniques, and it is shown that the solution is unstable. To address this instability, three one-parameter families of regularization operators are proposed, each designed to counteract the factors responsible for the instability of the inverse operator. Additionally, a new rule for selecting the regularization parameter is introduced, and an error bound is derived for each estimate. Numerical examples with varying characteristics are provided to illustrate the advantages of the proposed strategies.
本文基于在任意位置进行的噪声时变测量,对由时间分数抛物方程描述的输运过程中识别时变源项的问题进行了数学研究。利用傅里叶技术对该问题进行了解析求解,结果表明该解是不稳定的。为了解决这种不稳定性,提出了三个单参数正则化算子族,每个正则化算子族都被设计用来抵消导致逆算子不稳定性的因素。此外,还引入了正则化参数的选择规则,并给出了每个估计的误差范围。给出了具有不同特征的数值算例来说明所提出策略的优点。
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引用次数: 0
Global optimality of 3- and 5-point Fibonacci lattices for quasi-Monte Carlo integration and general energies 拟蒙特卡罗积分和一般能量的3点和5点斐波那契格的全局最优性
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-12-05 DOI: 10.1016/j.jco.2025.102012
Nicolas Nagel
We use linear programming bounds to analyze point sets in the torus with respect to their optimality for problems in discrepancy theory and quasi-Monte Carlo methods. These concepts will be unified by introducing tensor product energies.
We show that the canonical 3-point lattice in any dimension is globally optimal among all 3-point sets in the torus with respect to a large class of such energies. This is a new instance of universal optimality, a special phenomenon that is only known for a small class of highly structured point sets.
In the case of d=2 dimensions it is conjectured that so-called Fibonacci lattices should also be optimal with respect to a large class of potentials. To this end we show that the 5-point Fibonacci lattice is globally optimal for a continuously parametrized class of potentials relevant to the analysis of the quasi-Monte Carlo method.
针对差异理论和拟蒙特卡罗方法中的问题,利用线性规划界分析环面上点集的最优性。这些概念将通过引入张量积能量统一起来。我们证明了任何维度的正则3点格在环面上的所有3点集合中对于一类这样的能量是全局最优的。这是普遍最优性的一个新实例,它是一种特殊的现象,只存在于一小类高度结构化的点集中。在d=2维的情况下,我们推测所谓的斐波那契格对于一大类势也应该是最优的。为此,我们证明了5点Fibonacci晶格对于与准蒙特卡罗方法分析相关的连续参数化类势是全局最优的。
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引用次数: 0
Special Issue of the Journal of Complexity 复杂性杂志特刊
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-11-28 DOI: 10.1016/j.jco.2025.102002
Josef Dick (Guest Editors), Michael Gnewuch, Erich Novak, Leszek Plaskota, Jan Vybíral
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引用次数: 0
On recovering the Radon-Nikodym derivative under the big data assumption 大数据假设下Radon-Nikodym导数的恢复
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-11-17 DOI: 10.1016/j.jco.2025.102001
Hanna L. Myleiko , Sergei G. Solodky
The present paper is focused on recovering the Radon-Nikodym derivative under the big data assumption. To address the above problem, we design an algorithm that is a combination of the Nyström subsampling and the standard Tikhonov regularization. The convergence rate of the corresponding algorithm is established both in the case when the Radon-Nikodym derivative belongs to RKHS and in the case when it does not. We prove that the proposed approach not only ensures the order of accuracy as algorithms based on the whole sample size, but also allows to achieve subquadratic computational costs in the number of observations.
本文主要研究在大数据假设下Radon-Nikodym导数的恢复问题。为了解决上述问题,我们设计了一种结合Nyström子采样和标准Tikhonov正则化的算法。建立了Radon-Nikodym导数属于RKHS和不属于RKHS两种情况下相应算法的收敛速度。我们证明了所提出的方法不仅保证了基于整个样本量的算法的精度顺序,而且允许在观测数上实现次二次的计算成本。
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引用次数: 0
Weighted sampling recovery of functions with mixed smoothness 混合光滑函数的加权抽样恢复
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-11-12 DOI: 10.1016/j.jco.2025.102000
Dinh Dũng
We studied linear weighted sampling algorithms and their optimality for approximate recovery of functions with mixed smoothness on Rd from a set of n their sampled values. Functions to be recovered are in weighted Sobolev spaces Wp,wr(Rd) of mixed smoothness, and the approximation error is measured by the norm of the weighted Lebesgue space Lq,w(Rd). Here, the weight w is a tensor-product Freud-type weight. The optimality of linear sampling algorithms is investigated in terms of sampling n-widths. We constructed linear sampling algorithms on sparse grids of sampled points which form a step hyperbolic cross in the function domain, and which give upper bounds for the corresponding sampling n-widths. We proved that in the one-dimensional case, these algorithms realize the exact convergence rate of the n-sampling widths.
我们研究了线性加权抽样算法及其从n个采样值中近似恢复Rd上混合光滑函数的最优性。待恢复函数位于混合平滑的加权Sobolev空间Wp,wr(Rd)中,逼近误差由加权Lebesgue空间Lq,w(Rd)的范数来测量。这里,权值w是一个张量积弗洛伊德型权值。从采样宽度的角度研究了线性采样算法的最优性。我们构造了在函数域中形成阶梯双曲交叉的采样点稀疏网格上的线性采样算法,并给出了相应采样宽度的上界。我们证明了在一维情况下,这些算法实现了n个采样宽度的精确收敛速率。
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引用次数: 0
Marcinkiewicz–Zygmund inequalities in quasi-Banach function spaces 拟banach函数空间中的Marcinkiewicz-Zygmund不等式
IF 1.8 2区 数学 Q1 MATHEMATICS Pub Date : 2025-11-05 DOI: 10.1016/j.jco.2025.101999
Yurii Kolomoitsev , Sergey Tikhonov
We obtain Marcinkiewicz–Zygmund (MZ) inequalities in various Banach and quasi-Banach spaces under minimal structural assumptions. Our main results show that the Bernstein inequality in a general quasi-Banach function lattice X implies Marcinkiewicz–Zygmund type estimates in X. We present a unified approach to deriving MZ inequalities not only for polynomials, but also for other function classes, including entire functions of exponential type, splines, exponential sums, and more. As applications, we derive error estimates for sampling operators, Nikolskii-type inequalities, as well as inequalities for best approximations and moduli of smoothness.
在最小结构假设下,我们得到了各种Banach和拟Banach空间中的Marcinkiewicz-Zygmund (MZ)不等式。我们的主要结果表明,一般拟banach函数格X中的Bernstein不等式暗示了X中的Marcinkiewicz-Zygmund型估计。我们提出了一种统一的方法来推导多项式的MZ不等式,而且还推导了其他函数类的MZ不等式,包括指数型、样条、指数和等全函数。作为应用,我们推导了抽样算子的误差估计,nikolskii型不等式,以及最佳逼近不等式和平滑模。
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引用次数: 0
期刊
Journal of Complexity
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