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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. 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.

  6. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    e. In numerical analysis, finite-difference methods (FDM) are a class of numerical techniques for solving differential equations by approximating derivatives with finite differences. Both the spatial domain and time domain (if applicable) are discretized, or broken into a finite number of intervals, and the values of the solution at the end ...

  7. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    The derivative of the function at a point is the slope of the line tangent to the curve at the point. Slope of the constant function is zero, because the tangent line to the constant function is horizontal and its angle is zero. In other words, the value of the constant function, y, will not change as the value of x increases or decreases.

  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. Symmetric derivative - Wikipedia

    en.wikipedia.org/wiki/Symmetric_derivative

    In mathematics, the symmetric derivative is an operation generalizing the ordinary derivative. The expression under the limit is sometimes called the symmetric difference quotient. [ 3 ][ 4 ] A function is said to be symmetrically differentiable at a point x if its symmetric derivative exists at that point.