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  2. Logarithmic derivative - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_derivative

    with n an integer, n ≠ 0. The logarithmic derivative is then n / z {\displaystyle n/z} and one can draw the general conclusion that for f meromorphic, the singularities of the logarithmic derivative of f are all simple poles, with residue n from a zero of order n , residue − n from a pole of order n .

  3. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    The slope of the constant function is 0, because the tangent line to the constant function is horizontal and its angle is 0. In other words, the value of the constant function, y {\textstyle y} , will not change as the value of x {\textstyle x} increases or decreases.

  4. Logarithmic differentiation - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_differentiation

    In calculus, logarithmic differentiation or differentiation by taking logarithms is a method used to differentiate functions by employing the logarithmic derivative of a function f, [1] (⁡) ′ = ′ ′ = (⁡) ′.

  5. Derivative - Wikipedia

    en.wikipedia.org/wiki/Derivative

    In mathematics, the derivative is a fundamental tool that quantifies the sensitivity to change of a function's output with respect to its input. The derivative of a function of a single variable at a chosen input value, when it exists, is the slope of the tangent line to the graph of the function at that point.

  6. Leibniz integral rule - Wikipedia

    en.wikipedia.org/wiki/Leibniz_integral_rule

    Suppose a and b are constant, and that f(x) involves a parameter α which is constant in the integration but may vary to form different integrals. Assume that f(x, α) is a continuous function of x and α in the compact set {(x, α) : α 0 ≤ α ≤ α 1 and a ≤ x ≤ b}, and that the partial derivative f α (x, α) exists and is

  7. 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.

  8. Notation for differentiation - Wikipedia

    en.wikipedia.org/wiki/Notation_for_differentiation

    It is particularly common when the equation y = f(x) is regarded as a functional relationship between dependent and independent variables y and x. Leibniz's notation makes this relationship explicit by writing the derivative as: [ 1 ] d y d x . {\displaystyle {\frac {dy}{dx}}.}

  9. Differential of a function - Wikipedia

    en.wikipedia.org/wiki/Differential_of_a_function

    the partial differential of y with respect to any one of the variables x 1 is the principal part of the change in y resulting from a change dx 1 in that one variable. The partial differential is therefore involving the partial derivative of y with respect to x 1.