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Related papers: Chebyshev approximation by non-Chebyshev systems

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There is presented an approach to find an approximation polynomial of a function with two variables based on the two dimensional discrete Fourier transform. The approximation polynomial is expressed through Chebyshev polynomials. There is…

Numerical Analysis · Mathematics 2015-04-21 Ernest Scheiber

We consider the problem of approximating an analytic function on a compact interval from its values at $M+1$ distinct points. When the points are equispaced, a recent result (the so-called impossibility theorem) has shown that the best…

Numerical Analysis · Mathematics 2018-04-09 Ben Adcock , Rodrigo Platte , Alexei Shadrin

We prove an analogue of Chebyshev's alternation theorem for linearly independent discrete functions $\Phi_n=\{\varphi_k\}_{k=1}^n$ on the interval $[0,q]_{\mathbb{Z}}=[0,q]\cap \mathbb{Z}$. In particular, we establish that the polynomial of…

Classical Analysis and ODEs · Mathematics 2025-01-07 D. V. Gorbachev , V. I. Ivanov , S. Yu. Tikhonov

This paper presents a computationally efficient model predictive control formulation that uses an integral Chebyshev collocation method to enable rapid operations of autonomous agents. By posing the finite-horizon optimal control problem…

Robotics · Computer Science 2025-03-26 Deep Parikh , Thomas L. Ahrens , Manoranjan Majji

In this paper we provide new quantum algorithms with polynomial speed-up for a range of problems for which no such results were known, or we improve previous algorithms. First, we consider the approximation of the frequency moments $F_k$ of…

Quantum Physics · Physics 2019-07-08 Yassine Hamoudi , Frédéric Magniez

This document introduces a strategy to solve linear optimization problems. The strategy is based on the bounding condition each constraint produces on each one of the problem's dimension. The solution of a linear optimization problem is…

Optimization and Control · Mathematics 2018-09-24 Gerardo L. Febres

The problem of computing optimal orthogonal approximation to a given matrix has attracted growing interest in machine learning. Notable applications include the recent Muon optimizer or Riemannian optimization on the Stiefel manifold. Among…

Numerical Analysis · Mathematics 2026-02-25 Ekaterina Grishina , Matvey Smirnov , Maxim Rakhuba

Estimating the Domain of Attraction (DA) of non-polynomial systems is a challenging problem. Taylor expansion is widely adopted for transforming a nonlinear analytic function into a polynomial function, but the performance of Taylor…

Systems and Control · Computer Science 2017-09-18 Dongkun Han , Dimitra Panagou

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

We present a one-step algorithm that solves the Maxwell equations for systems with spatially varying permittivity and permeability by the Chebyshev method. We demonstrate that this algorithm may be orders of magnitude more efficient than…

Computational Physics · Physics 2009-11-07 H. De Raedt , K. Michielsen , J. S. Kole , M. T. Figge

We consider the problem of finding a best uniform approximation to the standard monomial on the unit ball in $\bbC^2$ by polynomials of lower degree with complex coefficients. We reduce the problem to a one-dimensional weighted minimization…

Classical Analysis and ODEs · Mathematics 2010-02-11 I. Moale , P. Yuditskii

We consider a decision-making problem to find absolute ratings of alternatives that are compared in pairs under multiple criteria, subject to constraints in the form of two-sided bounds on ratios between the ratings. Given matrices of…

Optimization and Control · Mathematics 2024-03-22 Nikolai Krivulin

We consider problems with multiple linear objectives and linear constraints and use Adjustable Robust Optimization and Polynomial Optimization as tools to approximate the Pareto set with polynomials of arbitrarily large degree. The main…

Optimization and Control · Mathematics 2015-01-13 Bram L. Gorissen , Dick den Hertog

We consider the problem of estimating the support size of a discrete distribution whose minimum non-zero mass is at least $ \frac{1}{k}$. Under the independent sampling model, we show that the sample complexity, i.e., the minimal sample…

Statistics Theory · Mathematics 2016-12-13 Yihong Wu , Pengkun Yang

We study a class of combinatorial scheduling problems characterized by a particular type of constraint often associated with electrical power or gas energy. This constraint appears in several practical applications and is expressed as a sum…

Data Structures and Algorithms · Computer Science 2023-12-27 Trung Thanh Nguyen , Khaled Elbassioni , Areg Karapetyan , Majid Khonji

In this paper, we demonstrate the application of generalised rational uniform (Chebyshev) approximation in neural networks. In particular, our activation functions are one degree rational functions and the loss function is based on the…

Optimization and Control · Mathematics 2021-11-05 Vinesha Peiris

This letter presents a method for synthesizing equiripple MIMO transmit beampatterns using Chebyshev approximation. The MIMO beampattern is represented as a non-negative real-valued trigonometric polynomial where the $\ell^{\text{th}}$…

Signal Processing · Electrical Eng. & Systems 2025-06-05 David A. Hague , David G. Felton

Previous works show convergence of rational Chebyshev approximants to the Pad\'e approximant as the underlying domain of approximation shrinks to the origin. In the present work, the asymptotic error and interpolation properties of rational…

Numerical Analysis · Mathematics 2024-10-08 Tobias Jawecki

For a function that is analytic on and around an interval, Chebyshev polynomial interpolation provides spectral convergence. However, if the function has a singularity close to the interval, the rate of convergence is near one. In these…

Numerical Analysis · Mathematics 2017-08-10 Kevin W. Aiton , Tobin A. Driscoll

Bernstein polynomial approximation to a continuous function has a slower rate of convergence as compared to other approximation methods. "The fact seems to have precluded any numerical application of Bernstein polynomials from having been…

Optimization and Control · Mathematics 2018-12-18 Venanzio Cichella , Isaac Kaminer , Claire Walton , Naira Hovakimyan , Antonio Pascoal