ergonomics 发表于 2025-3-21 16:09:08
书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0390743<br><br> <br><br>书目名称Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0390743<br><br> <br><br>capsule 发表于 2025-3-21 20:29:25
https://doi.org/10.1007/978-3-319-17205-7y formulated eigenvalue problems. These algorithms have a common feature: they consider the angle between the exact eigenspace and the approximate one, thereby enabling them to handle cases where eigenvalues are tightly clustered.Evolve 发表于 2025-3-22 02:34:54
,Lehmann–Goerisch Method for High-Precision Eigenvalue Bounds,ained from the lower bound derived in Chaps. . and .. This method takes the advantage of accurate approximate eigenfunctions computed by any means and subsequently delivers precise eigenvalue bounds. The effectiveness of this method is demonstrated via its application to the Laplacian and Steklov eigenvalue problems.屈尊 发表于 2025-3-22 06:21:37
Guaranteed Eigenfunction Computation,y formulated eigenvalue problems. These algorithms have a common feature: they consider the angle between the exact eigenspace and the approximate one, thereby enabling them to handle cases where eigenvalues are tightly clustered.folliculitis 发表于 2025-3-22 09:52:42
https://doi.org/10.1007/978-981-13-8051-8ation allow for the use of both conforming and non-conforming FEMs to solve various problems, such as the biharmonic eigenvalue problem, the Steklov eigenvalue problem, and the Maxwell eigenvalue problem, with diverse function settings.intimate 发表于 2025-3-22 15:57:03
http://reply.papertrans.cn/40/3908/390743/390743_6.pngintimate 发表于 2025-3-22 17:25:00
https://doi.org/10.1007/978-3-662-09901-8ogress in the field of guaranteed eigenvalue computation over the past decade, while also highlighting its relationship with early work such as Birkhoff’s result. Examples of eigenvalue problems demonstrate the need for guaranteed computation. The chapter also discusses the settings of function spaces and basic usage of finite element methods.叫喊 发表于 2025-3-22 22:03:57
The System Silicon-Nitrogen-Hydrogen partial differential equations. These error estimates are crucial for obtaining explicit eigenvalue bounds. A primary focus is on the a priori error estimation based on the hypercircle method (i.e., the Prager–Synge theorem), offering a novel approach for projection error estimation in the analysis of eigenvalue problems.相信 发表于 2025-3-23 03:56:26
http://reply.papertrans.cn/40/3908/390743/390743_9.png健谈 发表于 2025-3-23 09:08:30
Introduction to Eigenvalue Problems,ogress in the field of guaranteed eigenvalue computation over the past decade, while also highlighting its relationship with early work such as Birkhoff’s result. Examples of eigenvalue problems demonstrate the need for guaranteed computation. The chapter also discusses the settings of function spaces and basic usage of finite element methods.