
arXiv: 1909.13565
Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates a unified approach to these techniques, utilizing partial sums of the Taylor series in a high arithmetic precision. In particular, the proposed approach is capable of interpolation, extrapolation, numerical differentiation, numerical integration, solution of ordinary and partial differential equations, and system identification. The method employs Taylor polynomials and hundreds of digits in the computations to obtain precise results. Interestingly, some well-known problems are found to arise in the calculation accuracy and not methodological inefficiencies, as would be expected. In particular, the approximation errors are precisely predictable, the Runge phenomenon is eliminated, and the extrapolation extent may a priory be anticipated. The attained polynomials offer a precise representation of the unknown system as well as its radius of convergence, which provides a rigorous estimation of the prediction ability. The approximation errors are comprehensively analyzed for a variety of calculation digits and test problems and can be reproduced by the provided computer code.
inverse problems, Taylor polynomials, extrapolation, function approximation, QA75.5-76.95, Numerical Analysis (math.NA), ordinary differential equation, interpolation, partial differential equation, Electronic computers. Computer science, Taylor series, numerical integration, FOS: Mathematics, approximation errors, Mathematics - Numerical Analysis, numerical differentiation, system identification
inverse problems, Taylor polynomials, extrapolation, function approximation, QA75.5-76.95, Numerical Analysis (math.NA), ordinary differential equation, interpolation, partial differential equation, Electronic computers. Computer science, Taylor series, numerical integration, FOS: Mathematics, approximation errors, Mathematics - Numerical Analysis, numerical differentiation, system identification
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