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  2. Finite difference coefficient - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_coefficient

    Backward finite difference [ edit ] To get the coefficients of the backward approximations from those of the forward ones, give all odd derivatives listed in the table in the previous section the opposite sign, whereas for even derivatives the signs stay the same.

  3. Finite difference - Wikipedia

    en.wikipedia.org/wiki/Finite_difference

    In an analogous way, one can obtain finite difference approximations to higher order derivatives and differential operators. For example, by using the above central difference formula for f ′(x + ⁠ h / 2 ⁠) and f ′(x − ⁠ h / 2 ⁠) and applying a central difference formula for the derivative of f ′ at x, we obtain the central difference approximation of the second derivative of f:

  4. Divided differences - Wikipedia

    en.wikipedia.org/wiki/Divided_differences

    In mathematics, divided differences is an algorithm, historically used for computing tables of logarithms and trigonometric functions. [citation needed] Charles Babbage's difference engine, an early mechanical calculator, was designed to use this algorithm in its operation. [1] Divided differences is a recursive division process.

  5. MacCormack method - Wikipedia

    en.wikipedia.org/wiki/MacCormack_method

    The order of differencing can be reversed for the time step (i.e., forward/backward followed by backward/forward). For nonlinear equations, this procedure provides the best results. For linear equations, the MacCormack scheme is equivalent to the Lax–Wendroff method. [4]

  6. FTCS scheme - Wikipedia

    en.wikipedia.org/wiki/FTCS_scheme

    In numerical analysis, the FTCS (forward time-centered space) method is a finite difference method used for numerically solving the heat equation and similar parabolic partial differential equations. [1] It is a first-order method in time, explicit in time, and is conditionally stable when applied to the heat equation.

  7. Central differencing scheme - Wikipedia

    en.wikipedia.org/wiki/Central_differencing_scheme

    Figure 1.Comparison of different schemes. In applied mathematics, the central differencing scheme is a finite difference method that optimizes the approximation for the differential operator in the central node of the considered patch and provides numerical solutions to differential equations. [1]

  8. Time-scale calculus - Wikipedia

    en.wikipedia.org/wiki/Time-scale_calculus

    The forward jump, backward jump, and graininess operators on a discrete time scale The forward jump and backward jump operators represent the closest point in the time scale on the right and left of a given point t {\displaystyle t} , respectively.

  9. Difference quotient - Wikipedia

    en.wikipedia.org/wiki/Difference_quotient

    The difference between two points, themselves, is known as their Delta (ΔP), as is the difference in their function result, the particular notation being determined by the direction of formation: Forward difference: ΔF(P) = F(P + ΔP) − F(P); Central difference: δF(P) = F(P + ⁠ 1 / 2 ⁠ ΔP) − F(P − ⁠ 1 / 2 ⁠ ΔP);