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作者机构:Pearl River Community Coll Hattiesburg MS 39401 USA Univ So Mississippi Dept Math Hattiesburg MS 39406 USA
出 版 物:《LINEAR ALGEBRA AND ITS APPLICATIONS》 (线性代数及其应用)
年 卷 期:2015年第468卷
页 面:233-259页
核心收录:
学科分类:07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题:Lanczos algorithm Spectral methods Gaussian quadrature Heat equation Wave equation
摘 要:The stiffness of systems of ODEs that arise from spatial discretization of PDEs causes difficulties for both explicit and implicit time-stepping methods. Krylov Subspace Spectral (KSS) methods present a balance between the efficiency of explicit methods and the stability of implicit methods by computing each Fourier coefficient from an individualized approximation of the solution operator of the PDE. While KSS methods are explicit methods that exhibit a high order of accuracy and stability similar to that of implicit methods, their efficiency needs to be improved. A previous asymptotic study of block Lanczos iteration yielded estimates of extremal block Gaussian quadrature nodes for each Fourier component and led to an improvement in efficiency. In this paper, a more detailed asymptotic study is performed in order to rapidly estimate all nodes, thus drastically reducing computational expense without sacrificing accuracy. Numerical results demonstrate that the new node estimation scheme does in fact accomplish these aims. (C) 2014 Elsevier Inc. All rights reserved.