In this section, we concentrate on the polynomials obtained by degenerating only the numerator part of Daehee numbers and polynomials.
end{aligned} (4 where (S_j x)) is the transfer function as a function of the frequency x on an interval ([x_j, x_{j+1}], x_j) is the jth frequency at which the calibration data are available, (a_j, b_j, c_j), and (d_j) are the coefficients of the polynomials obtained by the cubic spline interpolation, and M is the number of data points of the calibration table.
In this paper, firstly, we introduce a new set of bivariate orthogonal polynomials, obtained by the product tensor of Racah polynomials defined on non-uniform lattice by Tchebichef, Krawtchouk polynomials, both defined on uniform lattice, and dual Hahn polynomials defined on non-uniform lattice.
In addition, this corollary complements the estimates on the expected number of zeros of Gaussian random harmonic polynomials obtained by Li and Wei in [13] and, more recently, by Lerario and Lundberg in [11].
A set of polynomials obtained by this method can be used to represent the structure of manifold pattern.
Furthermore, we introduce the matrix representation of some results for higher-order Daehee numbers and polynomials obtained by Kim et al. [8] in terms of Stirling numbers, Nörlund numbers, and Bernoulli numbers of higher order and give simple and short proofs of these results.
We present an algorithm for deciding the x-order of intersections from the signs of the coefficients of a polynomial, obtained by a general approach based on resultants.
The formulated locking free element uses higher order interpolating polynomial obtained by solving static part of the coupled governing differential equations.
Open image in new window Fig. 3 The plot of the logarithm (base 10) of the absolute error between the function (xmapsto |cos x|^{1/4}), and (left) its Fourier projection (right) trigonometric polynomial obtained by our summability operator, where the Fourier coefficients are estimated by 128 point FFT.
The influence of various parameters pressure, initial CO2 concentration, gas-to-liquid ratios, and temperature on the CO2 removal efficiency and its absorption rate in water were investigated and estimated thoroughly by statistical polynomial models obtained by the utilization of the response surface method (RS M with a central composite design (CCD).
