linear polynomial 
In this paper a representation for linear polynomial projection is given.


Depending on the formulation of the problem, its solution takes the form either of a system of bilinear polynomial equations, or system of linear polynomial equations, or finite formulas.


Exact estimates of approximation of periodic functions by linear polynomial methods of convolution type


Several remarks on the norms of linear polynomial operators


Approximation error for linear polynomial interpolation onnsimplices


LetP1,n(f;x) be the linear polynomial interpolatingf at the vertices of the simplex.


On conservative approximation by linear polynomial operators an extension of the Bernstein's operator


In this work we study linear polynomial operators preserving some consecutive iconvexities and leaving invariant the polynomials up to a certain degree.


Response surface methodology was adopted and an empirical linear polynomial model constructed on the basis of the specific uptake (mg of metal/g of biomass as dry weight) for each metal species.


Simultaneously, the mode functions are expanded into a uniform convergence series and a linear polynomial, so that the problem of convergence and differentiation of mode series is solved.


Because the pressure distribution could be expressed as an one order linear polynomial, the iterative expression of elastic deformation deduced by this method is simple, and the numerical accuracy is higher.


Thus the question of convergence forh→0 is closely connected to the linear (polynomial) case.


However it differs from GFDM by using a sequence of two first order numerical derivations based on linear polynomial basis instead of a second order derivation based on a quadratic polynomial basis.


We have implemented the proposed nonlinear (polynomial regression) statistical intervalvalued type2 FLS to perform smart washing machine control.


The Hermite rational interpolation is described in terms of linear polynomial projections.


A note on the approximation inC2π by linear polynomial operators


On a Jackson type theorem in several variables for linear polynomial approximation


In this paper, we prove that there does not exist a set with more than 26 polynomials with integer coefficients, such that the product of any two of them plus a linear polynomial is a square of a polynomial with integer coefficients.


This is applied to classify all the conservation laws for linear polynomial evolution equations of arbitrary order.


This paper deals with the computation of the formally integrable systems underlying a given quasilinear polynomial DAE.

