Global Approximation

2007 ◽  
pp. 99-118
Author(s):  
Giampiero Mastinu ◽  
Massimiliano Gobbi ◽  
Carlo Miano
Keyword(s):  
Global Approximation

A Global Approximation Theorem for Meyer-K�nig and Zeller operators

1978 ◽  
Vol 160 (3) ◽  
pp. 195-206 ◽  
Author(s):  
Michael Becker ◽  
Rolf J. Nessel
Keyword(s):  
Approximation Theorem ◽  
Global Approximation

An Efficient Operational Matrix Technique for Multidimensional Variable-Order Time Fractional Diffusion Equations

2016 ◽  
Vol 11 (6) ◽  
Author(s):  
M. A. Zaky ◽  
S. S. Ezz-Eldien ◽  
E. H. Doha ◽  
J. A. Tenreiro Machado ◽  
A. H. Bhrawy
Keyword(s):  
Present Method ◽  
Operational Matrix ◽  
Solution Process ◽  
Fractional Diffusion ◽  
Diffusion Equations ◽  
Variable Order ◽  
Algebraic Equations ◽  
Global Approximation ◽  
Fractional Diffusion Equations ◽  
Accurate Numerical Algorithm

This paper derives a new operational matrix of the variable-order (VO) time fractional partial derivative involved in anomalous diffusion for shifted Chebyshev polynomials. We then develop an accurate numerical algorithm to solve the 1 + 1 and 2 + 1 VO and constant-order fractional diffusion equation with Dirichlet conditions. The contraction of the present method is based on shifted Chebyshev collocation procedure in combination with the derived shifted Chebyshev operational matrix. The main advantage of the proposed method is to investigate a global approximation for spatial and temporal discretizations, and it reduces such problems to those of solving a system of algebraic equations, which greatly simplifies the solution process. In addition, we analyze the convergence of the present method graphically. Finally, comparisons between the algorithm derived in this paper and the existing algorithms are given, which show that our numerical schemes exhibit better performances than the existing ones.

Global Approximation: Performance Comparison of Different Methods, With an Application to Road Vehicle System Engineering

1999 ◽  
Author(s):  
Massimiliano Gobbi ◽  
Giampiero Mastinu
Keyword(s):  
Neural Networks ◽  
Mathematical Model ◽  
Linear Interpolation ◽  
Performance Comparison ◽  
Pareto Optimal ◽  
Approximation Methods ◽  
Global Approximation ◽  
Road Vehicle ◽  
Pareto Optimal Set ◽  
Design Variables

Abstract Optimisation of complex mechanical systems has often to be performed by resorting to global approximation. In usual global approximation practice, the original mathematical model is substituted by another mathematical model which gives approximately the same relationships between design variables and performance indexes. This is made to ensure much faster simulations which are of crucial importance to find optimal solutions. In this paper the performances of four global approximation methods (Neural Networks, Kriging, Quadratic Approximation, Linear Interpolation) are compared, with reference to an actual optimal design problem. The performances of a road vehicle suspension system are optimised by varying the system’s design variables. The Pareto-optimal set is derived symbolically. The performances of the different approximation methods taken into consideration are assessed by comparing the numerical- and the analytical-Pareto-optimal results. It is found that Neural Networks obtain the best accuracy.

scholarly journals Vortex reconnections in classical and quantum fluids

SeMA Journal ◽  
2021 ◽  
Author(s):  
Alberto Enciso ◽  
Daniel Peralta-Salas
Keyword(s):  
Stokes Equations ◽  
Quantum Fluids ◽  
Navier Stokes ◽  
Pitaevskii Equation ◽  
Global Approximation ◽  
Rigorous Results ◽  
Navier Stokes Equations ◽  
Localization Principle ◽  
Global Smooth Solutions ◽  
Vortex Reconnection

AbstractWe review recent rigorous results on the phenomenon of vortex reconnection in classical and quantum fluids. In the context of the Navier–Stokes equations in $$\mathbb {T}^3$$ T 3 we show the existence of global smooth solutions that exhibit creation and destruction of vortex lines of arbitrarily complicated topologies. Concerning quantum fluids, we prove that for any initial and final configurations of quantum vortices, and any way of transforming one into the other, there is an initial condition whose associated solution to the Gross–Pitaevskii equation realizes this specific vortex reconnection scenario. Key to prove these results is an inverse localization principle for Beltrami fields and a global approximation theorem for the linear Schrödinger equation.

A two-stage approximation strategy for piecewise smooth functions in two and three dimensions

2021 ◽  
Author(s):  
Sergio Amat ◽  
David Levin ◽  
Juan Ruiz-Álvarez
Keyword(s):  
Piecewise Smooth ◽  
Three Dimensions ◽  
System Of Equations ◽  
Global Approximation ◽  
Smooth Functions ◽  
Approximation Techniques ◽  
Second Stage ◽  
Principle Of Matching ◽  
The Given ◽  
Standard Approximation

Abstract Given values of a piecewise smooth function $f$ on a square grid within a domain $[0,1]^d$, $d=2,3$, we look for a piecewise adaptive approximation to $f$. Standard approximation techniques achieve reduced approximation orders near the boundary of the domain and near curves of jump singularities of the function or its derivatives. The insight used here is that the behavior near the boundaries, or near a singularity curve, is fully characterized and identified by the values of certain differences of the data across the boundary and across the singularity curve. We refer to these values as the signature of $f$. In this paper, we aim at using these values in order to define the approximation. That is, we look for an approximation whose signature is matched to the signature of $f$. Given function data on a grid, assuming the function is piecewise smooth, first, the singularity structure of the function is identified. For example, in the two-dimensional case, we find an approximation to the curves separating between smooth segments of $f$. Secondly, simultaneously, we find the approximations to the different segments of $f$. A system of equations derived from the principle of matching the signature of the approximation and the function with respect to the given grid defines a first stage approximation. A second stage improved approximation is constructed using a global approximation to the error obtained in the first stage approximation.

Global Approximation Results

1988 ◽  
pp. 275-314 ◽  
Author(s):  
Claudio Canuto ◽  
M. Yousuff Hussaini ◽  
Alfio Quarteroni ◽  
Thomas A. Zang
Keyword(s):  
Global Approximation
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