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Lanczos algorithm explained in statistics 统计学解释Lanczos算法
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100666
Qiang Niu , Mianmian Chen , Jinheng Wu
The Lanczos algorithm is a well-known three-term recurrence that can be used to generate an orthogonal basis for a Krylov subspace derived by a symmetric matrix. In the paper, we present a statistical interpretation of the entries of the tridiagonal matrix generated by the Lanczos process with a diagonal matrix X and an initial vector e. We show that the entries on the main diagonal line can be interpreted as weighted mean and the entries on the super-diagonal line can be understood as weighted sum of variance. Besides, a recurrence for producing the entries on the off-diagonal entries of the tridiagonal matrix is discovered, which leads to a new implementation of the Lanczos process. Finally, numerical examples are provided to investigate the preservation of orthogonality and efficiency in data fitting.
Lanczos算法是一种著名的三项递归算法,可以用来生成由对称矩阵导出的Krylov子空间的正交基。本文用一个对角矩阵X和一个初始向量e对Lanczos过程生成的三对角矩阵的条目进行了统计解释。我们证明主对角线上的条目可以解释为加权均值,超对角线上的条目可以理解为加权方差和。此外,还发现了在三对角矩阵的非对角项上产生项的递归式,从而给出了Lanczos过程的一种新的实现方法。最后,给出了数值算例来研究数据拟合中保持正交性和效率的问题。
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引用次数: 0
Optimal error estimates of BDF2 finite element method for the two-dimensional time-dependent Schrödinger equation 二维时间相关Schrödinger方程的BDF2有限元法最优误差估计
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100663
Zhikun Tian , Jianyun Wang , Zixin Zhong
In this paper, we investigate the two-step backward differentiation formula (BDF2) finite element method for a two-dimensional time-dependent Schrödinger equation. By applying the finite element method for space discretization and the BDF2 for time discretization, we derive a fully discrete scheme for the Schrödinger equation. The errors of the exact solution with the finite element solution are divided into temporal and spatial errors for separate analysis. We obtain the optimal error estimate in both space and time for the fully discrete scheme. Finally, a numerical experiment is performed to demonstrate the accuracy and efficiency of the proposed numerical scheme.
本文研究了二维时间相关Schrödinger方程的两步向后微分公式(BDF2)有限元法。利用空间离散化的有限元方法和时间离散化的BDF2方法,导出了Schrödinger方程的完全离散格式。将精确解与有限元解的误差分为时间误差和空间误差进行单独分析。我们得到了全离散格式在空间和时间上的最优误差估计。最后,通过数值实验验证了所提数值格式的准确性和有效性。
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引用次数: 0
Analytical and numerical investigation of wave resonance over rectangular basin with submerged triangular breakwaters 三角形防波堤淹没下矩形盆地波浪共振的解析与数值研究
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100655
Ikha Magdalena , Anwar Efendi Nasution
Wave resonance in coastal basins can cause significant environmental and structural damage, highlighting the need for effective mitigation strategies in coastal engineering. This study explores resonance phenomena in a rectangular semi-closed basin protected by submerged triangular breakwaters. The wave dynamics are modeled utilizing modified Linear Shallow Water Equations (LSWEs), which incorporate a breakwater-induced friction factor. Analytical and numerical approaches are employed in determining the basin’s natural period—a key parameter governing the onset of resonance. Numerical simulations, formulated utilizing the finite volume method, are conducted to identify the conditions that trigger resonance. The findings reveal that submerged triangular breakwaters substantially affect the natural period and help attenuate resonance effects, providing valuable insights for the design of resilient coastal infrastructure.
沿海盆地的波浪共振可能造成严重的环境和结构破坏,因此需要在沿海工程中制定有效的缓解策略。本研究探讨了被淹没的三角形防波堤保护的矩形半封闭盆地中的共振现象。波浪动力学利用修正的线性浅水方程(LSWEs)进行建模,其中包含了防波堤诱导的摩擦因子。分析和数值方法用于确定盆地的自然周期,这是控制共振发生的关键参数。利用有限体积法进行了数值模拟,以确定触发共振的条件。研究结果表明,水下三角形防波堤对自然周期有很大影响,有助于减弱共振效应,为弹性沿海基础设施的设计提供了有价值的见解。
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引用次数: 0
Second-order finite element discretization of Stokes equations on convex polygonal meshes 凸多边形网格上Stokes方程的二阶有限元离散化
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100672
Yanyan Song , Yanqiu Wang , Qiao Xin
In this paper, we construct two finite element discretizations on convex polygonal meshes for the Stokes equations, using the generalized barycentric coordinates (GBCs). Both constructions use a bubble-enhanced second-order Floater-Lai GBC to discretize the velocity field. The pressure field is discretized by discontinuous piecewise constants and discontinuous piecewise linears, respectively. They can be viewed as the generalization of the P2-P0 and the Q2-P1 elements to convex polygonal meshes. We prove the inf–sup stability and the optimal convergence for both discretizations. Supporting numerical results are presented.
本文利用广义质心坐标在凸多边形网格上构造了Stokes方程的两个有限元离散化。两种结构都使用气泡增强的二阶float - lai GBC来离散速度场。压力场分别采用不连续分段常数和不连续分段线性进行离散。它们可以看作是P2-P0和Q2-P1元素对凸多边形网格的推广。证明了这两种离散化方法的稳定性和最优收敛性。给出了相应的数值结果。
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引用次数: 0
Sparse PCA via matrix (2,1)-norm regularization with an application to feature selection 基于矩阵(2,1)范数正则化的稀疏PCA及其在特征选择中的应用
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100676
Li Wang , Jiawei Wang , Ren-Cang Li
This paper is concerned with sparse PCA via the matrix (2,1)-norm regularization (PCA2,1). It can produce a row-sparse projection, a useful tool in machine learning when it comes to, for example, feature selection, that aims to choose most relevant features. Mathematically, PCA2,1 is a non-smooth optimization problem on the Stiefel manifold. For a suitably chosen regularization parameter, the optimal projection matrix has many negligible rows. A practical NEPv approach (nonlinear eigenvalue problem with eigenvector dependency) is proposed to iteratively compute the optimal projection matrix. It is shown that the approach is globally convergent in the sense that the objective is monotonically increasing during the iterative process and any accumulation point of the iterates is a stationary point to the optimization problem. Extensive numerical experiments, with an application to feature selection, have been conducted to demonstrate the performance of the practical NEPv approach, with comparison against existing feature selection methods in terms of classification accuracy. The numerical results demonstrate that PCA2,1 is highly effective and often produces superior classification results to existing feature selection methods that are in use today.
本文通过矩阵(2,1)-范数正则化(PCA2,1)来研究稀疏主成分分析。它可以产生行稀疏投影,这是机器学习中一个有用的工具,例如,在特征选择方面,它旨在选择最相关的特征。在数学上,PCA2,1是Stiefel流形上的非光滑优化问题。对于适当选择的正则化参数,最优投影矩阵具有许多可忽略的行。提出了一种实用的NEPv方法(具有特征向量依赖的非线性特征值问题)来迭代计算最优投影矩阵。结果表明,该方法是全局收敛的,即在迭代过程中目标是单调递增的,迭代的任何累加点都是优化问题的平稳点。我们进行了大量的数值实验,并将其应用于特征选择,以证明实际NEPv方法的性能,并与现有的特征选择方法在分类精度方面进行了比较。数值结果表明,PCA2,1是非常有效的,并且通常比目前使用的现有特征选择方法产生更好的分类结果。
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引用次数: 0
A local meshless technique for recovering dual forms of time-varying sources in the nonlocal inverse heat equation 非局部逆热方程中时变源对偶形式的局部无网格恢复技术
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100673
Elyas Shivanian , Ahmad Jafarabadi , Mousa J. Huntul
This study focuses on retrieving a time-dependent source term in the heat equation governed by two distinct nonlocal boundary conditions. The inverse problem is structured with an interior energy over-specification constraint. The proposed computational framework combines the partition of unity approach for spatial discretization with the finite difference scheme for temporal advancement. Through energy analysis, the semi-discrete time-stepping formulation is proven to be unconditionally stable and convergent at a rate of O(δt). Despite being linear and uniquely solvable, the problem is inherently ill-posed, as slight disturbances in input data can induce significant errors in the reconstructed solution. To counteract this instability, Tikhonov regularization is implemented, yielding a stable approximation even under noisy data conditions. Moreover, a novel parameter selection strategy for the regularization is introduced, which surpasses standard methods by delivering substantially improved results. Numerical simulations corroborate the scheme’s robustness, demonstrating its accuracy with noise-free inputs and its resilience when handling contaminated measurements.
本研究的重点是在由两个不同的非局部边界条件控制的热方程中检索与时间相关的源项。该逆问题具有内部能量超规范约束。所提出的计算框架结合了空间离散化的单位分割法和时间推进的有限差分格式。通过能量分析,证明了半离散时步公式是无条件稳定的,并以0 (δt)的速率收敛。尽管该问题是线性且唯一可解的,但它本质上是病态的,因为输入数据中的轻微干扰会在重构解中引起显著误差。为了抵消这种不稳定性,Tikhonov正则化实现,即使在有噪声的数据条件下也能产生稳定的近似。此外,引入了一种新的正则化参数选择策略,该策略通过提供显着改善的结果来超越标准方法。数值模拟证实了该方案的鲁棒性,证明了其在无噪声输入下的准确性以及在处理污染测量时的弹性。
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引用次数: 0
α-scaled strong convergence of stochastic theta method for stochastic differential equations driven by time-changed Lévy noise beyond Lipschitz continuity 时变lsamvy噪声驱动的随机微分方程的α尺度强收敛性
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100665
Jingwei Chen
This paper develops an α-parametrized framework for analyzing the strong convergence of the stochastic theta (ST) method for stochastic differential equations driven by time-changed Lévy noise (TCSDEwLNs). The analysis accommodates time–space-dependent coefficients satisfying local Lipschitz conditions. Properties of the inverse subordinator E are investigated and explicit moment bounds for the exact solution are derived with jump rate incorporated. The analysis demonstrates that the ST method converges strongly with order of min{ηF,ηG,ηH,α/2}, establishing a precise relationship between numerical accuracy and the time-change mechanism. This theoretical advancement extends existing results and facilitates applications in finance, physics and biology where time-changed Lévy models are prevalent.
本文建立了一个α-参数化框架,用于分析时变lsamvy噪声驱动的随机微分方程随机θ (ST)方法的强收敛性。该分析考虑了满足局部利普希茨条件的时空相关系数。研究了逆次元E的性质,导出了包含跳跃率的精确解的显式矩界。分析表明,ST方法在min{ηF,ηG,ηH,α/2}阶上有很强的收敛性,建立了数值精度与时变机理之间的精确关系。这一理论的进步扩展了现有的结果,并促进了在金融、物理和生物领域的应用,在这些领域,时间变化的lsamvy模型是普遍存在的。
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引用次数: 0
Turing conditions for a two-component isotropic growing system from a potential function 二组分各向同性势函数生长系统的图灵条件
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100664
Aldo Ledesma-Durán, Consuelo García-Alcántara, Iván Santamaría-Holek
We analyze pattern formation in a two-component system within an isotropically growing or shrinking domain. By studying the evolution of a Lyapunov-like function, we derive time-dependent Turing bifurcation conditions through a stability analysis of linear perturbations across all Fourier modes. This general framework enables explicit characterization of pattern formation dynamics. Numerically, we consider two cases: a steady base state (exponential growth) and a time-dependent state (linear growth). First, we validate our approach by recovering the well-known conditions for fixed domains. Then, we simulate the Brusselator reaction system in dynamic domains, obtaining excellent agreement with our model’s predictions. These simulations highlight key pattern features, including evolution, amplitude growth, and wavenumber inertia. Our findings provide a novel energetic and geometrical perspective on the Turing bifurcation.
我们分析了各向同性增长或收缩域内双组分系统的模式形成。通过研究类李雅普诺夫函数的演化,我们通过对所有傅立叶模式的线性扰动的稳定性分析,导出了随时间变化的图灵分岔条件。这个通用框架可以明确地描述模式形成的动态。在数值上,我们考虑两种情况:稳定的基态(指数增长)和随时间变化的状态(线性增长)。首先,我们通过恢复固定域的已知条件来验证我们的方法。在此基础上,对动力学域的Brusselator反应系统进行了模拟,结果与模型的预测结果非常吻合。这些模拟突出了关键的模式特征,包括演化、振幅增长和波数惯性。我们的发现为图灵分叉提供了一种新的能量和几何视角。
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引用次数: 0
Analytical solutions for time-fractional Cauchy problem based on OU, CIR and Jacobi processes with time-dependent parameters 基于OU、CIR和Jacobi过程的时间分数阶Cauchy问题解析解
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100657
Muntiranee Mongkolsin , Khamron Mekchay , Phiraphat Sutthimat
An analytical approach to solve a time-fractional Cauchy problem of order 0<α1 based on the Ornstein–Uhlenbeck (OU), Cox–Ingersoll–Ross (CIR) and Jacobi processes with time-dependent parameters by transforming it into a system of linear fractional differential equations is established. We consider the process as an inhomogeneous Pearson diffusion and derive the analytical formulas for conditional expectations via the Volterra fractional integral equation. We also provide the β-conditional moments of the OU, CIR and Jacobi processes where βR. Finally, we illustrate with examples of the first and second moments of the extended OU and extended CIR processes by obtaining solutions with different α values and comparing to α=1.
建立了一种基于具有时变参数的Ornstein-Uhlenbeck (OU)、Cox-Ingersoll-Ross (CIR)和Jacobi过程求解0阶<;α≤1阶时间分数阶Cauchy问题的解析方法,将其转化为线性分数阶微分方程系统。我们将此过程视为非齐次皮尔逊扩散,并通过Volterra分数阶积分方程推导出条件期望的解析公式。我们还给出了β∈R的OU、CIR和Jacobi过程的β-条件矩。最后,通过得到α值不同的解并与α=1进行比较,给出了扩展OU和扩展CIR过程的一阶矩和二阶矩的例子。
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引用次数: 0
Enhancing the Euler–Maruyama integrator via a balancing strategy for stochastic Volterra integral equations 利用平衡策略增强随机Volterra积分方程的Euler-Maruyama积分器
IF 1.3 Q2 MATHEMATICS, APPLIED Pub Date : 2025-11-01 DOI: 10.1016/j.rinam.2025.100671
Hassan Ranjbar, Afshin Babaei
This paper develops the balanced Euler–Maruyama integrator for stochastic Volterra integral equations. First, an upper bound for the designed integrator is rigorously established in the mean square sense. Next, the scheme is proved to give a strong convergence rate of 1/2 for general diffusion matrices. Furthermore, for a special case of diffusion matrices, we theoretically detect that the established integrator super-converges with strong order 1.0. Numerical experiments are provided to confirm the theoretical findings.
本文发展了随机Volterra积分方程的平衡Euler-Maruyama积分器。首先,在均方意义上严格地建立了所设计积分器的上界。其次,证明了该方案对于一般扩散矩阵具有1/2的强收敛速率。进一步,对于扩散矩阵的一种特殊情况,我们从理论上证明了所建立的积分器具有强阶1.0的超收敛性。数值实验验证了理论结果。
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引用次数: 0
期刊
Results in Applied Mathematics
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