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  2. Notation for differentiation - Wikipedia

    en.wikipedia.org/wiki/Notation_for_differentiation

    However, because integration is the inverse operation of differentiation, Lagrange's notation for higher order derivatives extends to integrals as well. Repeated integrals of f may be written as f ( − 1 ) ( x ) {\displaystyle f^{(-1)}(x)} for the first integral (this is easily confused with the inverse function f − 1 ( x ) {\displaystyle f ...

  3. Derivative - Wikipedia

    en.wikipedia.org/wiki/Derivative

    The higher order derivatives can be applied in physics; for example, while the first derivative of the position of a moving object with respect to time is the object's velocity, how the position changes as time advances, the second derivative is the object's acceleration, how the velocity changes as time advances.

  4. Differential of a function - Wikipedia

    en.wikipedia.org/wiki/Differential_of_a_function

    Informally, this motivates Leibniz's notation for higher-order derivatives () =. When the independent variable x itself is permitted to depend on other variables, then the expression becomes more complicated, as it must include also higher order differentials in x itself.

  5. Fourth, fifth, and sixth derivatives of position - Wikipedia

    en.wikipedia.org/wiki/Fourth,_fifth,_and_sixth...

    The higher-order derivatives are less common than the first three; [1] [2] thus their names are not as standardized, though the concept of a minimum snap trajectory has been used in robotics. [ 3 ] The fourth derivative is referred to as snap , leading the fifth and sixth derivatives to be "sometimes somewhat facetiously" [ 4 ] called crackle ...

  6. Product rule - Wikipedia

    en.wikipedia.org/wiki/Product_rule

    For two functions, it may be stated in Lagrange's notation as () ′ = ′ + ′ or in Leibniz's notation as () = +. The rule may be extended or generalized to products of three or more functions, to a rule for higher-order derivatives of a product, and to other contexts.

  7. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    Their algorithm is applicable to higher-order derivatives. A method based on numerical inversion of a complex Laplace transform was developed by Abate and Dubner. [21] An algorithm that can be used without requiring knowledge about the method or the character of the function was developed by Fornberg. [4]

  8. Inverse function rule - Wikipedia

    en.wikipedia.org/wiki/Inverse_function_rule

    In calculus, the inverse function rule is a formula that expresses the derivative of the inverse of a bijective and differentiable function f in terms of the derivative of f. More precisely, if the inverse of f {\displaystyle f} is denoted as f − 1 {\displaystyle f^{-1}} , where f − 1 ( y ) = x {\displaystyle f^{-1}(y)=x} if and only if f ...

  9. Leibniz's notation - Wikipedia

    en.wikipedia.org/wiki/Leibniz's_notation

    Similarly, the higher derivatives may be obtained inductively. While it is possible, with carefully chosen definitions, to interpret ⁠ dy / dx ⁠ as a quotient of differentials, this should not be done with the higher order forms. [17] However, an alternative Leibniz notation for differentiation for higher orders allows for this. [citation ...

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