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  2. Aitken's delta-squared process - Wikipedia

    en.wikipedia.org/wiki/Aitken's_delta-squared_process

    In numerical analysis, Aitken's delta-squared process or Aitken extrapolation is a series acceleration method used for accelerating the rate of convergence of a sequence. It is named after Alexander Aitken, who introduced this method in 1926. [1] It is most useful for accelerating the convergence of a sequence that is converging linearly.

  3. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2). In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite.

  4. Series acceleration - Wikipedia

    en.wikipedia.org/wiki/Series_acceleration

    Two classical techniques for series acceleration are Euler's transformation of series [1] and Kummer's transformation of series. [2] A variety of much more rapidly convergent and special-case tools have been developed in the 20th century, including Richardson extrapolation, introduced by Lewis Fry Richardson in the early 20th century but also known and used by Katahiro Takebe in 1722; the ...

  5. Rate of convergence - Wikipedia

    en.wikipedia.org/wiki/Rate_of_convergence

    In asymptotic analysis in general, one sequence () that converges to a limit is said to asymptotically converge to with a faster order of convergence than another sequence () that converges to in a shared metric space with distance metric | |, such as the real numbers or complex numbers with the ordinary absolute difference metrics, if

  6. Anderson acceleration - Wikipedia

    en.wikipedia.org/wiki/Anderson_acceleration

    In mathematics, Anderson acceleration, also called Anderson mixing, is a method for the acceleration of the convergence rate of fixed-point iterations.Introduced by Donald G. Anderson, [1] this technique can be used to find the solution to fixed point equations () = often arising in the field of computational science.

  7. Modified Richardson iteration - Wikipedia

    en.wikipedia.org/wiki/Modified_Richardson_iteration

    Modified Richardson iteration is an iterative method for solving a system of linear equations. Richardson iteration was proposed by Lewis Fry Richardson in his work dated 1910. It is similar to the Jacobi and Gauss–Seidel method. We seek the solution to a set of linear equations, expressed in matrix terms as =.

  8. Convergence tests - Wikipedia

    en.wikipedia.org/wiki/Convergence_tests

    While most of the tests deal with the convergence of infinite series, they can also be used to show the convergence or divergence of infinite products. This can be achieved using following theorem: Let { a n } n = 1 ∞ {\displaystyle \left\{a_{n}\right\}_{n=1}^{\infty }} be a sequence of positive numbers.

  9. Convergence proof techniques - Wikipedia

    en.wikipedia.org/wiki/Convergence_proof_techniques

    Convergence proof techniques are canonical patterns of mathematical proofs that sequences or functions converge to a finite limit when the argument tends to infinity.. There are many types of sequences and modes of convergence, and different proof techniques may be more appropriate than others for proving each type of convergence of each type of sequence.