Results 81 to 90 of about 43,913 (238)
Bernstein polynomials and learning theory
Let \(f(x)= -x\log x- (I- x)\log(1 - x)\) for \(0\leq x\leq 1\); it is referred to as the entropy function. Let \(B_n[f]\) denote the nth Bernstein polynomial of \(f\). One half of the paper establishes the estimates \[ f(x)- B_n[f](x)\geq {1\over 2n}+ {1\over 20n^2 x(1-x)}- {1\over 12n^2}\text{ for }{15\over n}\leq x\leq 1-{15\over n}, \] \[ \lim_{n ...
Dietrich Braess, Tomas Sauer
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Approximation of Discontinuous Functions by Positive Linear Operators. A Probabilistic Approach
ABSTRACT We obtain approximation results for general positive linear operators satisfying mild conditions, when acting on discontinuous functions and absolutely continuous functions having discontinuous derivatives. The upper bounds, given in terms of a local first modulus of continuity, are best possible, in the sense that we can construct particular ...
J.A. Adell +2 more
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Efficient discontinuous Galerkin finite element methods via Bernstein polynomials [PDF]
Robert C. Kirby
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Area of Bernstein-Type Polynomials [PDF]
Bernstein polynomials in one variable are known to be total-variation diminishing when compared to the approximated function f. Here we consider the two variable case and give a counterexample to show they are not area-diminishing. Sufficient conditions are then given on a continuous function f to insure convergence in area. A similar theorem is proved
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A semi-parametric model for circular data based on mixtures of beta distributions [PDF]
This paper introduces a new, semi-parametric model for circular data, based on mixtures of shifted, scaled, beta (SSB) densities. This model is more general than the Bernstein polynomial density model which is well known to provide good approximations to
Jose Antonio Carnicero, Michael P. Wiper
core
Consistency of Bernstein Polynomial Posteriors
SummaryA Bernstein prior is a probability measure on the space of all the distribution functions on [0, 1]. Under very general assumptions, it selects absolutely continuous distribution functions, whose densities are mixtures of known beta densities. The Bernstein prior is of interest in Bayesian nonparametric inference with continuous data.
PETRONE, SONIA, WASSERMAN L.
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Constrained Path Planning for Soft Continuum Robots With Bernstein Surfaces
This manuscript presents a framework for trajectory generation for soft continuum robots using principles from optimal control. The problem is constrained over the partial differential kinematic equations of the Cosserat rod model, capturing all modes of
Maxwell Hammond +4 more
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Direct Estimate for Bernstein Polynomials
The following pointwise approximation for the Bernstein polynomials \(B_ n (f,x)= \sum_{k=0}^ n {\binom nk} x^ k (1-x)^{n -k} f(k/n)\) are proved: \[ | B_ n (f,x)- f(x)|\leq C\omega^ 2_{\varphi^ \lambda} (f, n^{-1/2} \varphi (x)^{1- \lambda}), \qquad 0\leq \lambda\leq 1, \quad \varphi(x)^ 2= x(1-x).
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Uniform And Pointwise Polynomial Inequalities In Regions With Asymptotically Conformal Curve
In this we continue studying the Nikolskii and Bernstein-Walsh type polynomial estimation in the Lebesgue spaces in the bounded and unbounded regions bounded by asymptotically conformal ...
P. Özkartepe
doaj
A new approach for solving Bratu’s problem
A numerical technique for one-dimensional Bratu’s problem is displayed in this work. The technique depends on Bernstein polynomial approximation. Numerical examples are exhibited to verify the efficiency and accuracy of the proposed technique.
Ghomanjani Fateme, Shateyi Stanford
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