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  2. Polynomial root-finding algorithms - Wikipedia

    en.wikipedia.org/wiki/Polynomial_root-finding...

    Multiple roots are highly sensitive, known to be ill-conditioned and inaccurate in numerical computation in general. A method by Zhonggang Zeng (2004), implemented as a MATLAB package, computes multiple roots and corresponding multiplicities of a polynomial accurately even if the coefficients are inexact. [3] [4] [5]

  3. Steffensen's method - Wikipedia

    en.wikipedia.org/wiki/Steffensen's_method

    % The fixed point iteration function is assumed to be input as an % inline function. % This function will calculate and return the fixed point, p, % that makes the expression f(x) = p true to within the desired % tolerance, tol. format compact % This shortens the output. format long % This prints more decimal places. for i = 1: 1000 % get ready ...

  4. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    This consists in using the last computed approximate values of the root for approximating the function by a polynomial of low degree, which takes the same values at these approximate roots. Then the root of the polynomial is computed and used as a new approximate value of the root of the function, and the process is iterated.

  5. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    For example, the function f(x) = x 20 − 1 has a root at 1. Since f ′(1) ≠ 0 and f is smooth, it is known that any Newton iteration convergent to 1 will converge quadratically. However, if initialized at 0.5, the first few iterates of Newton's method are approximately 26214, 24904, 23658, 22476, decreasing slowly, with only the 200th ...

  6. Durand–Kerner method - Wikipedia

    en.wikipedia.org/wiki/Durand–Kerner_method

    After iteration number 5 we have 4 correct decimals, and the subsequent iteration number 6 confirms that the computed roots are fixed. This general behaviour is characteristic for the method. Also notice that, in this example, the roots are used as soon as they are computed in each iteration.

  7. ITP method - Wikipedia

    en.wikipedia.org/wiki/ITP_Method

    Given a continuous function defined from [,] to such that () (), where at the cost of one query one can access the values of () on any given .And, given a pre-specified target precision >, a root-finding algorithm is designed to solve the following problem with the least amount of queries as possible:

  8. Muller's method - Wikipedia

    en.wikipedia.org/wiki/Muller's_method

    Muller's method is a recursive method that generates a new approximation of a root ξ of f at each iteration using the three prior iterations. Starting with three initial values x 0, x −1 and x −2, the first iteration calculates an approximation x 1 using those three, the second iteration calculates an approximation x 2 using x 1, x 0 and x −1, the third iteration calculates an ...

  9. List of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical-analysis...

    It provides a rich Excel-like user interface and its built-in vector programming language FPScript has a syntax similar to MATLAB. FreeMat, an open-source MATLAB-like environment with a GPL license. GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command-line interface for solving ...