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In numerical analysis, a numerical method is a mathematical tool designed to solve numerical problems. The implementation of a numerical method with an appropriate convergence check in a programming language is called a numerical algorithm.
The field of numerical analysis predates the invention of modern computers by many centuries. Linear interpolation was already in use more than 2000 years ago. Many great mathematicians of the past were preoccupied by numerical analysis, [5] as is obvious from the names of important algorithms like Newton's method, Lagrange interpolation polynomial, Gaussian elimination, or Euler's method.
Finite difference methods for heat equation and related PDEs: FTCS scheme (forward-time central-space) — first-order explicit; Crank–Nicolson method — second-order implicit; Finite difference methods for hyperbolic PDEs like the wave equation: Lax–Friedrichs method — first-order explicit; Lax–Wendroff method — second-order explicit
Numerical methods for solving first-order IVPs often fall into one of two large categories: [5] linear multistep methods, or Runge–Kutta methods.A further division can be realized by dividing methods into those that are explicit and those that are implicit.
The name is in analogy with quadrature, meaning numerical integration, where weighted sums are used in methods such as Simpson's rule 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. There ...
Numerical methods for ordinary differential equations, such as Runge–Kutta methods, can be applied to the restated problem and thus be used to evaluate the integral. For instance, the standard fourth-order Runge–Kutta method applied to the differential equation yields Simpson's rule from above.
Explicit and implicit methods are approaches used in numerical analysis for obtaining numerical approximations to the solutions of time-dependent ordinary and partial differential equations, as is required in computer simulations of physical processes.
In numerical analysis and applied mathematics, sinc numerical methods are numerical techniques [1] for finding approximate solutions of partial differential equations and integral equations based on the translates of sinc function and Cardinal function C(f,h) which is an expansion of f defined by