Journal of Computational and Applied Mathematics最新文献_第7页

Low-rank approximation: Randomized QR with Column Pivoting and related methods using sparse projection and pass-efficient techniques 低秩近似：随机QR与列枢轴和相关方法使用稀疏投影和传递效率技术

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117091

Ying Ji , Yuehua Feng , Yongxin Dong , Jinrui Guan , Xiao Han

引用次数: 0

Inexact block triangular preconditioners for double saddle-point systems arising from coupled Stokes–Darcy model 由耦合Stokes-Darcy模型引起的双鞍点系统的不精确块三角形预调节器

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117079

Siqi Liang, Na Huang

引用次数: 0

Codes equipped with non-cyclic burst-b distance, bounds and periodical burst errors 编码具有非循环突发距离、边界和周期性突发误差

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117081

Pankaj Kumar Das, Achal Agarwal

引用次数: 0

The backward problem of a stochastic space-fractional diffusion equation driven by fractional Brownian motion 分数阶布朗运动驱动的随机空间-分数阶扩散方程的后向问题

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117086

Fan Yang, Lu-Lu Yan, Xiao-Xiao Li

引用次数: 0

Componentwise and normwise perturbation analysis for the anti-triangular Schur decomposition 反三角Schur分解的分量和正态摄动分析

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117092

Jia Yan Wu , Xiao Shan Chen , Hai–Wei Sun

引用次数: 0

Convergence analysis of a PINNs-based approach to the inverse source problem of the heat equation with local measurements 基于pass的局部测量热方程逆源问题收敛性分析

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117077

Xuezhao Zhang, Zhiyuan Li

{"title":"Convergence analysis of a PINNs-based approach to the inverse source problem of the heat equation with local measurements","authors":"Xuezhao Zhang, Zhiyuan Li","doi":"10.1016/j.cam.2025.117077","DOIUrl":"10.1016/j.cam.2025.117077","url":null,"abstract":"<div><div>This paper investigates the problem of recovering the spatial distribution of the source term in a parabolic system from local measurement data. We propose a method based on Physics-Informed Neural Networks (PINNs) to approximate the solution of this inverse problem. Within this framework, we design a novel loss function that incorporates the residuals of the partial differential equation (PDE), measurement data residuals, as well as residuals from initial–boundary conditions and boundary derivatives. These additional terms enhance the regularity of the solution to address the ill-posedness of the inverse problem. Based on the conditional stability of the inverse problem, we demonstrate that the neural network can effectively approximate its solution, and we further establish generalization error estimates for the source term, which depend on the training error and data noise level, while also verifying the convergence of the network. A series of numerical experiments further validate the effectiveness and robustness of the proposed method, showing that it achieves high accuracy and efficiency under noisy data and varying measurement conditions.</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"476 ","pages":"Article 117077"},"PeriodicalIF":2.6,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A derivative-free spectral residual method for computing generalized eigenpairs of weakly symmetric tensors 计算弱对称张量广义特征对的无导数谱残差法

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117088

Ruijuan Zhao , Maolin Liang , Yangyang Xu , Qun Li

引用次数: 0

On numerical computation of inverses and determinants for generalized anti-tridiagonal Hankel matrices 广义反三对角汉克尔矩阵的逆和行列式的数值计算

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI: 10.1016/j.cam.2025.117076

Xin Fan, Ji-Teng Jia

引用次数: 0

Solving a system of quaternion matrix equations by using PSVD for multiple matrices with applications 用PSVD求解多矩阵的四元数矩阵方程组及其应用

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-22 DOI: 10.1016/j.cam.2025.117072

Zhuo-Heng He , Yun-Ze Xu , Qing-Wen Wang , Xiang-Xiang Wang

引用次数: 0

Curvature-guided cartoon-texture decomposition of a color image 彩色图像的曲率导向卡通纹理分解

IF 2.6 2区数学

Journal of Computational and Applied Mathematics Pub Date : 2025-09-22 DOI: 10.1016/j.cam.2025.117075

Jingjie Wang, Wei Wang

{"title":"Curvature-guided cartoon-texture decomposition of a color image","authors":"Jingjie Wang, Wei Wang","doi":"10.1016/j.cam.2025.117075","DOIUrl":"10.1016/j.cam.2025.117075","url":null,"abstract":"<div><div>In this paper, we propose a novel curvature-guided variational model for color image decomposition. In particular, we integrate the curvature priors into the traditional variational model to steer the evolution towards preserving curvature information, meanwhile, we incorporate saturation-value total variation to regularize the cartoon component of a color image. Additionally, we utilize the <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>1</mn></mrow></msup></math></span> norm to model the texture component in the saturation-value color space. The proposed variational model introduces an energy functional to achieve cartoon and texture decomposition in saturation-value color space, and preserves color information, fine structures/edges in the cartoon component. Theoretically, we explore the properties of the proposed model and provide a theoretical discussion about the existence of the solution. We then develop an effective and efficient algorithm to minimize the problem by utilizing the alternating direction method of multipliers. Numerical examples are presented to demonstrate that the performance of our framework competes favorably with other methods in terms of visual quality and metrics such as structure similarity (SSIM), peak signal-to-noise ratio (PSNR), quaternion structural similarity (QSSIM), S-CIELAB color metric, average local contrast (ALC), and discrete entropy (DE).</div></div>","PeriodicalId":50226,"journal":{"name":"Journal of Computational and Applied Mathematics","volume":"476 ","pages":"Article 117075"},"PeriodicalIF":2.6,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0