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  2. Total derivative - Wikipedia

    en.wikipedia.org/wiki/Total_derivative

    In many situations, this is the same as considering all partial derivatives simultaneously. The term "total derivative" is primarily used when f is a function of several variables, because when f is a function of a single variable, the total derivative is the same as the ordinary derivative of the function. [1]: 198–203

  3. General Leibniz rule - Wikipedia

    en.wikipedia.org/wiki/General_Leibniz_rule

    With the multi-index notation for partial derivatives of functions of several variables, the Leibniz rule states more generally: =: () ().. This formula can be used to derive a formula that computes the symbol of the composition of differential operators.

  4. Multivariable calculus - Wikipedia

    en.wikipedia.org/wiki/Multivariable_calculus

    The partial derivative generalizes the notion of the derivative to higher dimensions. A partial derivative of a multivariable function is a derivative with respect to one variable with all other variables held constant. [1]: 26ff A partial derivative may be thought of as the directional derivative of the function along a coordinate axis.

  5. Matrix calculus - Wikipedia

    en.wikipedia.org/wiki/Matrix_calculus

    In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices.It collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that can be treated as single entities.

  6. Chain rule - Wikipedia

    en.wikipedia.org/wiki/Chain_rule

    In calculus, the chain rule is a formula that expresses the derivative of the composition of two differentiable functions f and g in terms of the derivatives of f and g.More precisely, if = is the function such that () = (()) for every x, then the chain rule is, in Lagrange's notation, ′ = ′ (()) ′ (). or, equivalently, ′ = ′ = (′) ′.

  7. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    [a] Functionals are often expressed as definite integrals involving functions and their derivatives. Functions that maximize or minimize functionals may be found using the Euler–Lagrange equation of the calculus of variations. A simple example of such a problem is to find the curve of shortest length connecting two points.

  8. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    It gives simple arithmetic formulas to accurately compute values of many transcendental functions such as the exponential function and trigonometric functions. It is the starting point of the study of analytic functions , and is fundamental in various areas of mathematics, as well as in numerical analysis and mathematical physics .

  9. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    For example, [5] the first derivative can be calculated by the complex-step derivative formula: [12] [13] [14] ′ = ((+)) + (),:= The recommended step size to obtain accurate derivatives for a range of conditions is h = 10 − 200 {\displaystyle h=10^{-200}} . [ 6 ]