enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. Romberg's method - Wikipedia

    en.wikipedia.org/wiki/Romberg's_method

    Download QR code; Print/export ... it may be preferable to replace the polynomial interpolation of Richardson with the rational ... (in the C programming ...

  4. 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.

  5. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    In numerical analysis, polynomial interpolation is the interpolation of a given bivariate data set by the polynomial of lowest possible degree that passes through the points of the dataset. [ 1 ]

  6. 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]

  7. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    In the sixth iteration, we cannot use inverse quadratic interpolation because b 5 = b 4. Hence, we use linear interpolation between (a 5, f(a 5)) = (−3.35724, −6.78239) and (b 5, f(b 5)) = (−2.71449, 3.93934). The result is s = −2.95064, which satisfies all the conditions. But since the iterate did not change in the previous step, we ...

  8. 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.

  9. 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.