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  2. Laurent Schwartz - Wikipedia

    en.wikipedia.org/wiki/Laurent_Schwartz

    Laurent-Moïse Schwartz (French: [lɔʁɑ̃ mɔiz ʃvaʁts]; 5 March 1915 – 4 July 2002) was a French mathematician.He pioneered the theory of distributions, which gives a well-defined meaning to objects such as the Dirac delta function.

  3. Distribution (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Distribution_(mathematics)

    Gårding (1997) comments that although the ideas in the transformative book by Schwartz (1951) were not entirely new, it was Schwartz's broad attack and conviction that distributions would be useful almost everywhere in analysis that made the difference. A detailed history of the theory of distributions was given by Lützen (1982).

  4. Schwartz kernel theorem - Wikipedia

    en.wikipedia.org/wiki/Schwartz_kernel_theorem

    In mathematics, the Schwartz kernel theorem is a foundational result in the theory of generalized functions, published by Laurent Schwartz in 1952. It states, in broad terms, that the generalized functions introduced by Schwartz (Schwartz distributions) have a two-variable theory that includes all reasonable bilinear forms on the space of test functions.

  5. Distribution (number theory) - Wikipedia

    en.wikipedia.org/wiki/Distribution_(number_theory)

    In algebra and number theory, a distribution is a function on a system of finite sets into an abelian group which is analogous to an integral: it is thus the algebraic analogue of a distribution in the sense of generalised function. The original examples of distributions occur, unnamed, as functions φ on Q/Z satisfying [1]

  6. Generalized function - Wikipedia

    en.wikipedia.org/wiki/Generalized_function

    An influential book on operational calculus was Oliver Heaviside's Electromagnetic Theory of 1899. When the Lebesgue integral was introduced, there was for the first time a notion of generalized function central to mathematics. An integrable function, in Lebesgue's theory, is equivalent to any other which is the same almost everywhere. That ...

  7. Central moment - Wikipedia

    en.wikipedia.org/wiki/Central_moment

    In probability theory and statistics, a central moment is a moment of a probability distribution of a random variable about the random variable's mean; that is, it is the expected value of a specified integer power of the deviation of the random variable from the mean. The various moments form one set of values by which the properties of a ...

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  9. Spaces of test functions and distributions - Wikipedia

    en.wikipedia.org/wiki/Spaces_of_test_functions...

    The set of tempered distributions forms a vector subspace of the space of distributions ′ and is thus one example of a space of distributions; there are many other spaces of distributions. There also exist other major classes of test functions that are not subsets of C c ∞ ( U ) , {\displaystyle C_{c}^{\infty }(U),} such as spaces of ...