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  2. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    The original use of interpolation polynomials was to approximate values of important transcendental functions such as natural logarithm and trigonometric functions.Starting with a few accurately computed data points, the corresponding interpolation polynomial will approximate the function at an arbitrary nearby point.

  3. SLEPc - Wikipedia

    en.wikipedia.org/wiki/SLEPc

    A solver based on polynomial interpolation that relies on PEP solvers. A solver based on rational interpolation (NLEIGS). MFN can be used to compute the action of a matrix function on a vector. A restarted Krylov solver.

  4. ITP method - Wikipedia

    en.wikipedia.org/wiki/ITP_Method

    In numerical analysis, the ITP method, short for Interpolate Truncate and Project, is the first root-finding algorithm that achieves the superlinear convergence of the secant method [1] while retaining the optimal [2] worst-case performance of the bisection method. [3]

  5. Neville's algorithm - Wikipedia

    en.wikipedia.org/wiki/Neville's_algorithm

    In mathematics, Neville's algorithm is an algorithm used for polynomial interpolation that was derived by the mathematician Eric Harold Neville in 1934. Given n + 1 points, there is a unique polynomial of degree ≤ n which goes through the given points. Neville's algorithm evaluates this polynomial.

  6. Aitken interpolation - Wikipedia

    en.wikipedia.org/wiki/Aitken_interpolation

    Aitken interpolation is an algorithm used for polynomial interpolation that was derived by the mathematician Alexander Aitken. It is similar to Neville's algorithm . See also Aitken's delta-squared process or Aitken extrapolation .

  7. Smoothstep - Wikipedia

    en.wikipedia.org/wiki/Smoothstep

    Smoothstep is a family of sigmoid-like interpolation and clamping functions commonly used in computer graphics, [1] [2] video game engines, [3] and machine learning. [ 4 ] The function depends on three parameters, the input x , the "left edge" and the "right edge", with the left edge being assumed smaller than the right edge.

  8. Bulirsch–Stoer algorithm - Wikipedia

    en.wikipedia.org/wiki/Bulirsch–Stoer_algorithm

    Bulirsch and Stoer recognized that using rational functions as fitting functions for Richardson extrapolation in numerical integration is superior to using polynomial functions because rational functions are able to approximate functions with poles rather well (compared to polynomial functions), given that there are enough higher-power terms in ...

  9. Simpson's rule - Wikipedia

    en.wikipedia.org/wiki/Simpson's_rule

    Download QR code; Print/export ... One can use Lagrange polynomial interpolation to find an expression for this polynomial, = ... Mobile view Jump to content ...