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  2. Finite-difference time-domain method - Wikipedia

    en.wikipedia.org/wiki/Finite-difference_time...

    Partial chronology of FDTD techniques and applications for Maxwell's equations. [5]year event 1928: Courant, Friedrichs, and Lewy (CFL) publish seminal paper with the discovery of conditional stability of explicit time-dependent finite difference schemes, as well as the classic FD scheme for solving second-order wave equation in 1-D and 2-D. [6]

  3. Gradient discretisation method - Wikipedia

    en.wikipedia.org/wiki/Gradient_discretisation_method

    In numerical mathematics, the gradient discretisation method (GDM) is a framework which contains classical and recent numerical schemes for diffusion problems of various kinds: linear or non-linear, steady-state or time-dependent. The schemes may be conforming or non-conforming, and may rely on very general polygonal or polyhedral meshes (or ...

  4. Time-scale calculus - Wikipedia

    en.wikipedia.org/wiki/Time-scale_calculus

    In mathematics, time-scale calculus is a unification of the theory of difference equations with that of differential equations, unifying integral and differential calculus with the calculus of finite differences, offering a formalism for studying hybrid systems.

  5. Discrete Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_Fourier_transform

    Eq.1 can also be evaluated outside the domain [,], and that extended sequence is -periodic.Accordingly, other sequences of indices are sometimes used, such as [,] (if is even) and [,] (if is odd), which amounts to swapping the left and right halves of the result of the transform.

  6. Z-transform - Wikipedia

    en.wikipedia.org/wiki/Z-transform

    In mathematics and signal processing, the Z-transform converts a discrete-time signal, which is a sequence of real or complex numbers, into a complex valued frequency-domain (the z-domain or z-plane) representation. [1] [2] It can be considered a discrete-time equivalent of the Laplace transform (the s-domain or s-plane). [3]

  7. Galerkin method - Wikipedia

    en.wikipedia.org/wiki/Galerkin_method

    In mathematics, in the area of numerical analysis, Galerkin methods are a family of methods for converting a continuous operator problem, such as a differential equation, commonly in a weak formulation, to a discrete problem by applying linear constraints determined by finite sets of basis functions.

  8. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    [1] [2] It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering [3] to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. [4] [5]

  9. Burgers' equation - Wikipedia

    en.wikipedia.org/wiki/Burgers'_equation

    Burgers' equation or Bateman–Burgers equation is a fundamental partial differential equation and convection–diffusion equation [1] occurring in various areas of applied mathematics, such as fluid mechanics, [2] nonlinear acoustics, [3] gas dynamics, and traffic flow. [4]