Multivariate approximation by polynomial and generalized rational functions

نویسندگان

چکیده

In this paper, we develop an optimization-based approach to multivariate Chebyshev approximation on a finite grid. We consider two models: polynomial and generalized rational approximation. the second case, approximations are ratios of linear forms basis functions not limited monomials. It is already known that in case grid corresponding optimization problems can be reduced solving programming problem, while area so well understood. paper demonstrate quasiconvex. This statement remains true even when Then apply bisection method, which general method for quasiconvex optimization. converges optimal solution with given precision. convex feasibility appearing solved using programming. Finally, compare deviation error computational time same number decision variables.

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ژورنال

عنوان ژورنال: Optimization

سال: 2022

ISSN: ['0974-0988']

DOI: https://doi.org/10.1080/02331934.2022.2044478