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  2. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    Polynomial interpolation also forms the basis for algorithms in numerical quadrature (Simpson's rule) and numerical ordinary differential equations (multigrid methods). In computer graphics , polynomials can be used to approximate complicated plane curves given a few specified points, for example the shapes of letters in typography .

  3. Newton polynomial - Wikipedia

    en.wikipedia.org/wiki/Newton_polynomial

    If the quadratic term is negligible—meaning that the linear term is sufficiently accurate without adding the quadratic term—then linear interpolation is sufficiently accurate. If the problem is sufficiently important, or if the quadratic term is nearly big enough to matter, then one might want to determine whether the sum of the quadratic ...

  4. Interpolation - Wikipedia

    en.wikipedia.org/wiki/Interpolation

    The simplest interpolation method is to locate the nearest data value, and assign the same value. In simple problems, this method is unlikely to be used, as linear interpolation (see below) is almost as easy, but in higher-dimensional multivariate interpolation, this could be a favourable choice for its speed and simplicity.

  5. Inverse quadratic interpolation - Wikipedia

    en.wikipedia.org/.../Inverse_quadratic_interpolation

    In numerical analysis, inverse quadratic interpolation is a root-finding algorithm, meaning that it is an algorithm for solving equations of the form f(x) = 0. The idea is to use quadratic interpolation to approximate the inverse of f. This algorithm is rarely used on its own, but it is important because it forms part of the popular Brent's method.

  6. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    In numerical analysis, Brent's method is a hybrid root-finding algorithm combining the bisection method, the secant method and inverse quadratic interpolation.It has the reliability of bisection but it can be as quick as some of the less-reliable methods.

  7. Lagrange polynomial - Wikipedia

    en.wikipedia.org/wiki/Lagrange_polynomial

    A better form of the interpolation polynomial for practical (or computational) purposes is the barycentric form of the Lagrange interpolation (see below) or Newton polynomials. Lagrange and other interpolation at equally spaced points, as in the example above, yield a polynomial oscillating above and below the true function.

  8. Simpson's rule - Wikipedia

    en.wikipedia.org/wiki/Simpson's_rule

    Simpson's 1/3 rule, also simply called Simpson's rule, is a method for numerical integration proposed by Thomas Simpson. It is based upon a quadratic interpolation and is the composite Simpson's 1/3 rule evaluated for =.

  9. QUICK scheme - Wikipedia

    en.wikipedia.org/wiki/Quick_scheme

    In computational fluid dynamics QUICK, which stands for Quadratic Upstream Interpolation for Convective Kinematics, is a higher-order differencing scheme that considers a three-point upstream weighted by quadratic interpolation for the cell face values.