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  2. Differentiable function - Wikipedia

    en.wikipedia.org/wiki/Differentiable_function

    A differentiable function. In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain.In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its domain.

  3. C0-semigroup - Wikipedia

    en.wikipedia.org/wiki/C0-semigroup

    In mathematical analysis, a C 0-semigroup, also known as a strongly continuous one-parameter semigroup, is a generalization of the exponential function.Just as exponential functions provide solutions of scalar linear constant coefficient ordinary differential equations, strongly continuous semigroups provide solutions of linear constant coefficient ordinary differential equations in Banach spaces.

  4. Differential of a function - Wikipedia

    en.wikipedia.org/wiki/Differential_of_a_function

    Product rule: For two differentiable functions f and g, () = +. An operation d with these two properties is known in abstract algebra as a derivation . They imply the power rule d ( f n ) = n f n − 1 d f {\displaystyle d(f^{n})=nf^{n-1}df} In addition, various forms of the chain rule hold, in increasing level of generality: [ 12 ]

  5. Derivative - Wikipedia

    en.wikipedia.org/wiki/Derivative

    A function of a real variable is differentiable at a point of its domain, if its domain contains an open interval containing ⁠ ⁠, and the limit = (+) exists. [2] This means that, for every positive real number ⁠ ⁠, there exists a positive real number such that, for every such that | | < and then (+) is defined, and | (+) | <, where the vertical bars denote the absolute value.

  6. Weak derivative - Wikipedia

    en.wikipedia.org/wiki/Weak_derivative

    Let be a function in the Lebesgue space ([,]).We say that in ([,]) is a weak derivative of if ′ = ()for all infinitely differentiable functions with () = =.. Generalizing to dimensions, if and are in the space () of locally integrable functions for some open set, and if is a multi-index, we say that is the -weak derivative of if

  7. Gradient theorem - Wikipedia

    en.wikipedia.org/wiki/Gradient_theorem

    The gradient theorem states that if the vector field F is the gradient of some scalar-valued function (i.e., if F is conservative), then F is a path-independent vector field (i.e., the integral of F over some piecewise-differentiable curve is dependent only on end points). This theorem has a powerful converse:

  8. Inverse function theorem - Wikipedia

    en.wikipedia.org/wiki/Inverse_function_theorem

    For functions of a single variable, the theorem states that if is a continuously differentiable function with nonzero derivative at the point ; then is injective (or bijective onto the image) in a neighborhood of , the inverse is continuously differentiable near = (), and the derivative of the inverse function at is the reciprocal of the derivative of at : ′ = ′ = ′ (()).

  9. Rademacher's theorem - Wikipedia

    en.wikipedia.org/wiki/Rademacher's_theorem

    Rademacher's theorem is a special case, due to the fact that any Lipschitz function on Ω is an element of the space W 1,∞ (Ω). [9] There is a version of Rademacher's theorem that holds for Lipschitz functions from a Euclidean space into an arbitrary metric space in terms of metric differentials instead of the usual derivative.