Norm-Preserving Dilations and Their Applications to Optimal Error Bounds

1982 ◽  
Vol 19 (3) ◽  
pp. 445-469 ◽  
Author(s):  
Chandler Davis ◽  
W. M. Kahan ◽  
H. F. Weinberger
Keyword(s):  
2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
François Dubeau

We present a unified way to obtain optimal error bounds for general interpolatory integration rules. The method is based on the Peano form of the error term when we use Taylor’s expansion. These bounds depend on the regularity of the integrand. The method of integration by parts “backwards” to obtain bounds is also discussed. The analysis includes quadrature rules with nodes outside the interval of integration. Best error bounds for composite integration rules are also obtained. Some consequences of symmetry are discussed.


2012 ◽  
Vol 218 (13) ◽  
pp. 7034-7051 ◽  
Author(s):  
Javier de Frutos ◽  
Bosco García-Archilla ◽  
Julia Novo

1996 ◽  
Vol 197 (3) ◽  
pp. 767-773 ◽  
Author(s):  
Yair Shapira ◽  
Avram Sidi ◽  
Moshe Israeli

2001 ◽  
Vol 11 (05) ◽  
pp. 883-901 ◽  
Author(s):  
WEIZHU BAO ◽  
XIAODONG WANG ◽  
KLAUS-JÜRGEN BATHE

The objective of this paper is to present a study of the solvability, stability and optimal error bounds of certain mixed finite element formulations for acoustic fluids. An analytical proof of the stability and optimal error bounds of a set of three-field mixed finite element discretizations is given, and the interrelationship between the inf–sup condition, including the numerical inf–sup test, and the eigenvalue problem pertaining to the natural frequencies is discussed.


2014 ◽  
Vol 40 (2) ◽  
pp. 281-305 ◽  
Author(s):  
Yutian Li ◽  
Saiyu Liu ◽  
Shuaixia Xu ◽  
Yuqiu Zhao
Keyword(s):  

2008 ◽  
Vol 8 (3) ◽  
pp. 279-293 ◽  
Author(s):  
M.T. NAIR ◽  
U. TAUTENHAHN

AbstractFor solving linear ill-posed problems with noisy data regularization methods are required. We analyze a simplified regularization scheme in Hilbert scales for operator equations with nonnegative self-adjoint operators. By exploiting the op-erator monotonicity of certain functions, order-optimal error bounds are derived that characterize the accuracy of the regularized approximations. These error bounds have been obtained under general smoothness conditions.


Sign in / Sign up

Export Citation Format

Share Document