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  2. Difference quotient - Wikipedia

    en.wikipedia.org/wiki/Difference_quotient

    Difference quotient. In single-variable calculus, the difference quotient is usually the name for the expression. which when taken to the limit as h approaches 0 gives the derivative of the function f. [1][2][3][4] The name of the expression stems from the fact that it is the quotient of the difference of values of the function by the ...

  3. Finite difference - Wikipedia

    en.wikipedia.org/wiki/Finite_difference

    A finite difference is a mathematical expression of the form f (x + b) − f (x + a).If a finite difference is divided by b − a, one gets a difference quotient.The approximation of derivatives by finite differences plays a central role in finite difference methods for the numerical solution of differential equations, especially boundary value problems.

  4. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    Therefore, the true derivative of f at x is the limit of the value of the difference quotient as the secant lines get closer and closer to being a tangent line: ′ = (+) (). Since immediately substituting 0 for h results in 0 0 {\displaystyle {\frac {0}{0}}} indeterminate form , calculating the derivative directly can be unintuitive.

  5. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    Differentiation is linear. For any functions and and any real numbers and , the derivative of the function with respect to is: In Leibniz's notation this is written as: Special cases include: The constant factor rule. The sum rule.

  6. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    For example, consider the ordinary differential equation ′ = + The Euler method for solving this equation uses the finite difference quotient (+) ′ to approximate the differential equation by first substituting it for u'(x) then applying a little algebra (multiplying both sides by h, and then adding u(x) to both sides) to get (+) + (() +).

  7. Quotient rule - Wikipedia

    en.wikipedia.org/wiki/Quotient_rule

    In calculus, the quotient rule is a method of finding the derivative of a function that is the ratio of two differentiable functions. [1][2][3] Let , where both f and g are differentiable and The quotient rule states that the derivative of h(x) is. It is provable in many ways by using other derivative rules.

  8. Finite difference coefficient - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_coefficient

    Arbitrary stencil points. For arbitrary stencil points and any derivative of order up to one less than the number of stencil points, the finite difference coefficients can be obtained by solving the linear equations [6] where is the Kronecker delta, equal to one if , and zero otherwise. Example, for , order of differentiation :

  9. Five-point stencil - Wikipedia

    en.wikipedia.org/wiki/Five-point_stencil

    In numerical analysis, given a square grid in one or two dimensions, the five-point stencil of a point in the grid is a stencil made up of the point itself together with its four "neighbors". It is used to write finite difference approximations to derivatives at grid points. It is an example for numerical differentiation.

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