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  2. SLEPc - Wikipedia

    en.wikipedia.org/wiki/SLEPc

    Polynomial filters for interior eigenvalues. SVD contains solvers for the singular value decomposition as well as the generalized singular value decomposition. Solvers based on the cross-product matrix or the cyclic matrix, that rely on EPS solvers. Specific solvers based on bidiagonalization such as Golub-Kahan-Lanczos and a thick-restarted ...

  3. Xcas - Wikipedia

    en.wikipedia.org/wiki/Xcas

    Here is a brief overview of what Xcas is able to do: [9] [10] Xcas has the ability of a scientific calculator that provides show input and writes pretty print; Xcas works also as a spreadsheet; [11]

  4. 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.

  5. 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.

  6. 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.

  7. Chebyshev nodes - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_nodes

    The Chebyshev nodes are important in approximation theory because they form a particularly good set of nodes for polynomial interpolation. Given a function f on the interval [, +] and points ,, …,, in that interval, the interpolation polynomial is that unique polynomial of degree at most which has value () at each point .

  8. Lebesgue constant - Wikipedia

    en.wikipedia.org/wiki/Lebesgue_constant

    The process of interpolation maps the function to a polynomial . This defines a mapping X {\displaystyle X} from the space C ([ a , b ]) of all continuous functions on [ a , b ] to itself. The map X is linear and it is a projection on the subspace Π n of polynomials of degree n or less.

  9. 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 .

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