Sentence examples for basis to approximate from inspiring English sources

Okabe et al. [18] used a Haar wavelet basis to approximate the lighting effect by a small number of basis functions.

First, we discretize the Caputo time fractional derivative by the usual finite difference formula and then use trigonometric cubic B-spline basis to approximate derivatives in space.

In the absence of empirical data to determine the exact values for the curvature parameter b i, we present a theoretical basis to define approximate parameters.

The Galerkin boundary node method is a boundary meshless method which uses MLS basis functions to approximate solution of problems.

Several numerical examples are considered to demonstrate the validity and applicability of the basis functions to approximate fractional derivatives (and integrals) of some functions.

For these computations, we use finite differences to discretize the time coordinate, a discrete ordinate method to discretize the directional variable, and an expansion in radial basis functions to approximate the spatial dependence of the solution.

Their originality lies in the use of rapidly-decaying spectral basis functions to approximate the vertical dependence of the solutions, combined with one (method A) or two (method B) slowly-decaying "extra functions" for each wave-vector that exactly represent the irrotational component of the solution at large distances.

For these problems defined in the unbounded time domain, we use the rational normalized Bernstein functions as basis functions to approximate the exact solution.

Two-dimensional orthogonal triangular functions are used in [3, 18] as a new set of basis functions to approximate solutions of nonlinear two-dimensional integral equations.

An alternative approach applicable for larger molecules is to use a series of high-level correlation calculations, such as QCISD(T), MP4 or CCSD(T), with moderate sized basis sets to approximate the result of a more expensive calculation.

In these figures, the circles represent observed RNA-seq expression signal (green: normal; red: cancer); the blues lines are Fourier basis expansion to approximate the observed signal using weighted least square methods.