A Lanczos method for approximating composite functions
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Publication:388581
DOI10.1016/j.amc.2012.05.009zbMath1283.65016arXiv1110.0058OpenAlexW2059879831MaRDI QIDQ388581
Paul G. Constantine, Eric T. Phipps
Publication date: 2 January 2014
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1110.0058
exponential functionnumerical exampleorthogonal polynomialsdimension reductionGaussian quadraturerational functionLanczos' methodNavier-Stokes model
Navier-Stokes equations for incompressible viscous fluids (76D05) Algorithms for approximation of functions (65D15) Approximate quadratures (41A55) Numerical quadrature and cubature formulas (65D32)
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- Non intrusive iterative stochastic spectral representation with application to compressible gas dynamics
- Time-dependent generalized polynomial chaos
- The numerically stable reconstruction of Jacobi matrices from spectral data
- Analysis of the symmetric Lanczos algorithm with reorthogonalization methods
- Behavior of slightly perturbed Lanczos and conjugate-gradient recurrences
- Matrices, moments and quadrature. II: How to compute the norm of the error iterative methods
- Large-scale stabilized FE computational analysis of nonlinear steady-state transport/reaction systems
- On sensitivity of Gauss-Christoffel quadrature
- Efficient descriptor-vector multiplications in stochastic automata networks
- The Lanczos Algorithm With Partial Reorthogonalization
- The Lanczos and conjugate gradient algorithms in finite precision arithmetic
- An overview of the Trilinos project
- Predicting the Behavior of Finite Precision Lanczos and Conjugate Gradient Computations
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- High-Order Collocation Methods for Differential Equations with Random Inputs
- The Lanczos and Conjugate Gradient Algorithms