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  2. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    For unit variance, the n-th derivative of the Gaussian is the Gaussian function itself multiplied by the n-th Hermite polynomial, up to scale. Consequently, Gaussian functions are also associated with the vacuum state in quantum field theory. Gaussian beams are used in optical systems, microwave systems and lasers.

  3. Distribution of the product of two random variables - Wikipedia

    en.wikipedia.org/wiki/Distribution_of_the...

    The area of the selection within the unit square and below the line z = xy, represents the CDF of z. This divides into two parts. The first is for 0 < x < z where the increment of area in the vertical slot is just equal to dx. The second part lies below the xy line, has y-height z/x, and incremental area dx z/x.

  4. Sum of normally distributed random variables - Wikipedia

    en.wikipedia.org/wiki/Sum_of_normally...

    To determine the value (), note that we rotated the plane so that the line x+y = z now runs vertically with x-intercept equal to c. So c is just the distance from the origin to the line x + y = z along the perpendicular bisector, which meets the line at its nearest point to the origin, in this case ( z / 2 , z / 2 ) {\displaystyle (z/2,z/2)\,} .

  5. 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.

  6. Multivariate normal distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_normal...

    Let z = (z 1, ..., z N) T be a vector whose components are N independent standard normal variates (which can be generated, for example, by using the Box–Muller transform). Let x be μ + Az . This has the desired distribution due to the affine transformation property.

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    A complex vector X ∈ C k is said to be normal if both its real and imaginary components jointly possess a 2k-dimensional multivariate normal distribution. The variance-covariance structure of X is described by two matrices: the variance matrix Γ, and the relation matrix C. Matrix normal distribution describes the case of normally distributed ...

  8. Gaussian filter - Wikipedia

    en.wikipedia.org/wiki/Gaussian_filter

    where the standard deviations are expressed in their physical units, e.g. in the case of time and frequency in seconds and hertz, respectively. In two dimensions, it is the product of two such Gaussians, one per direction: (,) = (+) / [3] [4] [5]

  9. List of integrals of Gaussian functions - Wikipedia

    en.wikipedia.org/wiki/List_of_integrals_of...

    In the previous two integrals, n!! is the double factorial: for even n it is equal to the product of all even numbers from 2 to n, and for odd n it is the product of all odd numbers from 1 to n; additionally it is assumed that 0!! = (−1)!! = 1.