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  2. Convolution theorem - Wikipedia

    en.wikipedia.org/wiki/Convolution_theorem

    In mathematics, the convolution theorem states that under suitable conditions the Fourier transform of a convolution of two functions (or signals) is the product of their Fourier transforms. More generally, convolution in one domain (e.g., time domain) equals point-wise multiplication in the other domain (e.g., frequency domain).

  3. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    A more precise version of the theorem quoted above requires specifying the class of functions on which the convolution is defined, and also requires assuming in addition that S must be a continuous linear operator with respect to the appropriate topology.

  4. List of theorems - Wikipedia

    en.wikipedia.org/wiki/List_of_theorems

    No free lunch theorem (philosophy of mathematics) No-hair theorem ; No-trade theorem ; No wandering domain theorem (ergodic theory) Noether's theorem (Lie groups, calculus of variations, differential invariants, physics) Noether's second theorem (calculus of variations, physics)

  5. Titchmarsh convolution theorem - Wikipedia

    en.wikipedia.org/wiki/Titchmarsh_convolution_theorem

    The original proof by Titchmarsh uses complex-variable techniques, and is based on the Phragmén–Lindelöf principle, Jensen's inequality, Carleman's theorem, and Valiron's theorem. The theorem has since been proven several more times, typically using either real-variable [3] [4] [5] or complex-variable [6] [7] [8] methods.

  6. Convolution of probability distributions - Wikipedia

    en.wikipedia.org/wiki/Convolution_of_probability...

    The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.

  7. Convolution power - Wikipedia

    en.wikipedia.org/wiki/Convolution_power

    If x is the distribution function of a random variable on the real line, then the n th convolution power of x gives the distribution function of the sum of n independent random variables with identical distribution x. The central limit theorem states that if x is in L 1 and L 2 with mean zero and variance σ 2, then

  8. Dirichlet convolution - Wikipedia

    en.wikipedia.org/wiki/Dirichlet_convolution

    Dirichlet convolution is a special case of the convolution multiplication for the incidence algebra of a poset, in this case the poset of positive integers ordered by divisibility. The Dirichlet hyperbola method computes the summation of a convolution in terms of its functions and their summation functions.

  9. Titchmarsh theorem - Wikipedia

    en.wikipedia.org/wiki/Titchmarsh_theorem

    In mathematics, particularly in the area of Fourier analysis, the Titchmarsh theorem may refer to: The Titchmarsh convolution theorem; The theorem relating real and imaginary parts of the boundary values of a H p function in the upper half-plane with the Hilbert transform of an L p function. See Hilbert transform#Titchmarsh's theorem