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  2. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    The name is in analogy with quadrature, meaning numerical integration, where weighted sums are used in methods such as Simpson's method or the Trapezoidal rule. There are various methods for determining the weight coefficients, for example, the Savitzky–Golay filter. Differential quadrature is used to solve partial differential equations ...

  3. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as " numerical integration ", although this term can also refer to the computation of integrals .

  4. Order of accuracy - Wikipedia

    en.wikipedia.org/wiki/Order_of_accuracy

    Using the big O notation an th-order accurate numerical method is notated as | | u − u h | | = O ( h n ) {\displaystyle ||u-u_{h}||=O(h^{n})} This definition is strictly dependent on the norm used in the space; the choice of such norm is fundamental to estimate the rate of convergence and, in general, all numerical errors correctly.

  5. Heun's method - Wikipedia

    en.wikipedia.org/wiki/Heun's_method

    In mathematics and computational science, Heun's method may refer to the improved [1] or modified Euler's method (that is, the explicit trapezoidal rule [2]), or a similar two-stage Runge–Kutta method. It is named after Karl Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value.

  6. Trapezoidal rule (differential equations) - Wikipedia

    en.wikipedia.org/wiki/Trapezoidal_rule...

    In numerical analysis and scientific computing, the trapezoidal rule is a numerical method to solve ordinary differential equations derived from the trapezoidal rule for computing integrals. The trapezoidal rule is an implicit second-order method, which can be considered as both a Runge–Kutta method and a linear multistep method.

  7. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    To use a finite difference method to approximate the solution to a problem, one must first discretize the problem's domain. This is usually done by dividing the domain into a uniform grid (see image). This means that finite-difference methods produce sets of discrete numerical approximations to the derivative, often in a "time-stepping" manner.

  8. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Numerov's methodfourth-order method for equations of the form ″ = (,) Predictor–corrector method — uses one method to approximate solution and another one to increase accuracy; General linear methods — a class of methods encapsulating linear multistep and Runge-Kutta methods

  9. Backward differentiation formula - Wikipedia

    en.wikipedia.org/wiki/Backward_differentiation...

    The backward differentiation formula (BDF) is a family of implicit methods for the numerical integration of ordinary differential equations.They are linear multistep methods that, for a given function and time, approximate the derivative of that function using information from already computed time points, thereby increasing the accuracy of the approximation.