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  2. File:Gauss-Seidel iteration sequence for two subsystems.pdf

    en.wikipedia.org/wiki/File:Gauss-Seidel...

    Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.

  3. Steffensen's method - Wikipedia

    en.wikipedia.org/wiki/Steffensen's_method

    The simplest form of the formula for Steffensen's method occurs when it is used to find a zero of a real function; that is, to find the real value that satisfies () =.Near the solution , the derivative of the function, ′, is supposed to approximately satisfy < ′ <; this condition ensures that is an adequate correction-function for , for finding its own solution, although it is not required ...

  4. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/Gauss–Seidel_method

    At any step in a Gauss-Seidel iteration, solve the first equation for in terms of , …,; then solve the second equation for in terms of just found and the remaining , …,; and continue to . Then, repeat iterations until convergence is achieved, or break if the divergence in the solutions start to diverge beyond a predefined level.

  5. Iteratively reweighted least squares - Wikipedia

    en.wikipedia.org/wiki/Iteratively_reweighted...

    IRLS can be used for ℓ 1 minimization and smoothed ℓ p minimization, p < 1, in compressed sensing problems. It has been proved that the algorithm has a linear rate of convergence for ℓ 1 norm and superlinear for ℓ t with t < 1, under the restricted isometry property, which is generally a sufficient condition for sparse solutions.

  6. L4 microkernel family - Wikipedia

    en.wikipedia.org/wiki/L4_microkernel_family

    Later the UNSW group, now at NICTA (formerly National ICT Australia, Ltd.), forked L4Ka::Pistachio into a new L4 version named NICTA::L4-embedded. It was for use in commercial embedded systems, and consequently the implementation trade-offs favored small memory size and reduced complexity. The API was modified to keep almost all system calls ...

  7. Laguerre's method - Wikipedia

    en.wikipedia.org/wiki/Laguerre's_method

    On the other hand, when is a multiple root convergence is merely linear, with the penalty of calculating values for the polynomial and its first and second derivatives at each stage of the iteration. A major advantage of Laguerre's method is that it is almost guaranteed to converge to some root of the polynomial no matter where the initial ...

  8. Relaxation (iterative method) - Wikipedia

    en.wikipedia.org/wiki/Relaxation_(iterative_method)

    While the method converges under general conditions, it typically makes slower progress than competing methods. Nonetheless, the study of relaxation methods remains a core part of linear algebra, because the transformations of relaxation theory provide excellent preconditioners for new methods.

  9. L-moment - Wikipedia

    en.wikipedia.org/wiki/L-moment

    Grouping these by order statistic counts the number of ways an element of an n element sample can be the j th element of an r element subset, and yields formulas of the form below. Direct estimators for the first four L-moments in a finite sample of n observations are: [ 7 ]