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  2. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/RungeKutta_methods

    In numerical analysis, the RungeKutta methods (English: / ˈrʊŋəˈkʊtɑː / ⓘ RUUNG-ə-KUUT-tah[1]) are a family of implicit and explicit iterative methods, which include the Euler method, used in temporal discretization for the approximate solutions of simultaneous nonlinear equations. [2]

  3. List of Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/List_of_RungeKutta_methods

    RungeKutta methods are methods for the numerical solution of the ordinary differential equation. Explicit RungeKutta methods take the form. Stages for implicit methods of s stages take the more general form, with the solution to be found over all s. Each method listed on this page is defined by its Butcher tableau, which puts the ...

  4. Runge–Kutta–Fehlberg method - Wikipedia

    en.wikipedia.org/wiki/RungeKutta–Fehlberg...

    In mathematics, the RungeKutta–Fehlberg method (or Fehlberg method) is an algorithm in numerical analysis for the numerical solution of ordinary differential equations. It was developed by the German mathematician Erwin Fehlberg and is based on the large class of RungeKutta methods. The novelty of Fehlberg's method is that it is an ...

  5. Cash–Karp method - Wikipedia

    en.wikipedia.org/wiki/Cash–Karp_method

    In numerical analysis, the Cash–Karp method is a method for solving ordinary differential equations (ODEs). It was proposed by Professor Jeff R. Cash [1] from Imperial College London and Alan H. Karp from IBM Scientific Center. The method is a member of the RungeKutta family of ODE solvers. More specifically, it uses six function ...

  6. Runge–Kutta method (SDE) - Wikipedia

    en.wikipedia.org/wiki/RungeKutta_method_(SDE)

    RungeKutta method (SDE) In mathematics of stochastic systems, the RungeKutta method is a technique for the approximate numerical solution of a stochastic differential equation. It is a generalisation of the RungeKutta method for ordinary differential equations to stochastic differential equations (SDEs).

  7. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    This guarantees stability if an integration scheme with a stability region that includes parts of the imaginary axis, such as the fourth order Runge-Kutta method, is used. This makes the SAT technique an attractive method of imposing boundary conditions for higher order finite difference methods, in contrast to for example the injection method ...

  8. Rate of convergence - Wikipedia

    en.wikipedia.org/wiki/Rate_of_convergence

    Convergence rate definitions. Suppose that the sequence converges to the number . The sequence is said to converge with order to , and with a rate of convergence , if. for some positive constant if and if . [2][4][5] It is not necessary that be an integer. For example, the secant method, when converging to a regular, simple root, has an order ...

  9. Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Linear_multistep_method

    Linear multistep method. Linear multistep methods are used for the numerical solution of ordinary differential equations. Conceptually, a numerical method starts from an initial point and then takes a short step forward in time to find the next solution point. The process continues with subsequent steps to map out the solution.