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  2. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    One may easily find points along W(x) at small values of x, and interpolation based on those points will yield the terms of W(x) and the specific product ab. As fomulated in Karatsuba multiplication, this technique is substantially faster than quadratic multiplication, even for modest-sized inputs, especially on parallel hardware.

  3. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    A simple two-point estimation is to compute the slope of a nearby secant line through the points (x, f(x)) and (x + h, f(x + h)). [1] Choosing a small number h , h represents a small change in x , and it can be either positive or negative.

  4. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    one can calculate a single point (e.g. the center of an image) using high-precision arithmetic (z), giving a reference orbit, and then compute many points around it in terms of various initial offsets delta plus the above iteration for epsilon, where epsilon-zero is set to 0.

  5. Numerical analysis - Wikipedia

    en.wikipedia.org/wiki/Numerical_analysis

    The field of numerical analysis predates the invention of modern computers by many centuries. Linear interpolation was already in use more than 2000 years ago. Many great mathematicians of the past were preoccupied by numerical analysis, [5] as is obvious from the names of important algorithms like Newton's method, Lagrange interpolation polynomial, Gaussian elimination, or Euler's method.

  6. Gaussian quadrature - Wikipedia

    en.wikipedia.org/wiki/Gaussian_quadrature

    The Gaussian quadrature chooses more suitable points instead, so even a linear function approximates the function better (the black dashed line). As the integrand is the third-degree polynomial y(x) = 7x 3 – 8x 2 – 3x + 3, the 2-point Gaussian quadrature rule even returns an exact result.

  7. Discontinuous Galerkin method - Wikipedia

    en.wikipedia.org/wiki/Discontinuous_Galerkin_method

    In applied mathematics, discontinuous Galerkin methods (DG methods) form a class of numerical methods for solving differential equations.They combine features of the finite element and the finite volume framework and have been successfully applied to hyperbolic, elliptic, parabolic and mixed form problems arising from a wide range of applications.

  8. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    The initial guess will be x 0 = 1 and the function will be f(x) = x 22 so that f ′ (x) = 2x. Each new iteration of Newton's method will be denoted by x1 . We will check during the computation whether the denominator ( yprime ) becomes too small (smaller than epsilon ), which would be the case if f ′ ( x n ) ≈ 0 , since otherwise a ...

  9. Nonstandard calculus - Wikipedia

    en.wikipedia.org/wiki/Nonstandard_calculus

    Let f be a continuous function on [a,b] such that f(a)<0 while f(b)>0. Then there exists a point c in [a,b] such that f(c)=0. The proof proceeds as follows. Let N be an infinite hyperinteger. Consider a partition of [a,b] into N intervals of equal length, with partition points x i as i runs from 0 to N. Consider the collection I of indices such ...