Ruimin Zhang , Lei Yang , Hui Zhu , Linghui Li , Yahong Wang
{"title":"An enhanced wavelet-based numerical scheme with higher convergence order for a class of high-order boundary value problems","authors":"Ruimin Zhang , Lei Yang , Hui Zhu , Linghui Li , Yahong Wang","doi":"10.1016/j.amc.2025.129602","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, a new numerical scheme is proposed to effectively solve a class of high-order boundary value problems (BVPs) with arbitrary orders and three types of boundary conditions. The method can reduce computational cost. By constructing an enhanced wavelet basis based on Legendre polynomials within a defined reproducing kernel space <span><math><msub><mrow><mi>W</mi></mrow><mrow><mi>m</mi></mrow></msub><mo>[</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>]</mo></math></span>, the <em>ε</em>-approximate solution of BVPs can be obtained applying the least squares method. These enhanced wavelets maintain compact support, ensuring superior approximation performance compared to classical wavelets. The convergence of the proposed scheme is characterized by its analytical order, while stability and complexity are also investigated. Specifically, for high-order nonlinear BVPs, the Quasi-Newton method is utilized effectively. We present numerical examples of several high-order linear and nonlinear BVPs with various boundary conditions, including Dirichlet, Neumann, and Robin conditions, to assess the stability and efficiency of the method. The numerical results show that our approach provides more accurate approximations, which are consistent with analytical solutions and show a high order of accuracy, outperforming several existing methods in the literature.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"507 ","pages":"Article 129602"},"PeriodicalIF":3.5000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325003285","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a new numerical scheme is proposed to effectively solve a class of high-order boundary value problems (BVPs) with arbitrary orders and three types of boundary conditions. The method can reduce computational cost. By constructing an enhanced wavelet basis based on Legendre polynomials within a defined reproducing kernel space , the ε-approximate solution of BVPs can be obtained applying the least squares method. These enhanced wavelets maintain compact support, ensuring superior approximation performance compared to classical wavelets. The convergence of the proposed scheme is characterized by its analytical order, while stability and complexity are also investigated. Specifically, for high-order nonlinear BVPs, the Quasi-Newton method is utilized effectively. We present numerical examples of several high-order linear and nonlinear BVPs with various boundary conditions, including Dirichlet, Neumann, and Robin conditions, to assess the stability and efficiency of the method. The numerical results show that our approach provides more accurate approximations, which are consistent with analytical solutions and show a high order of accuracy, outperforming several existing methods in the literature.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.