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  2. Geometric mean - Wikipedia

    en.wikipedia.org/wiki/Geometric_mean

    The geometric mean can also be expressed as the exponential of the arithmetic mean of logarithms. [4] By using logarithmic identities to transform the formula, the multiplications can be expressed as a sum and the power as a multiplication:

  3. Gauss–Legendre algorithm - Wikipedia

    en.wikipedia.org/wiki/Gauss–Legendre_algorithm

    The arithmetic–geometric mean of two numbers, a 0 and b 0, is found by calculating the limit of the sequences + = +, + =, which both converge to the same limit. If = and = ⁡ then the limit is (⁡) where () is the complete elliptic integral of the first kind

  4. Geometric mean filter - Wikipedia

    en.wikipedia.org/wiki/Geometric_mean_filter

    Each pixel of the output image at point (x,y) is given by the product of the pixels within the geometric mean mask raised to the power of 1/mn. For example, using a mask size of 3 by 3, pixel (x,y) in the output image will be the product of S(x,y) and all 8 of its surrounding pixels raised to the 1/9th power. Using the following original image ...

  5. Generalized mean - Wikipedia

    en.wikipedia.org/wiki/Generalized_mean

    The power mean could be generalized further to the generalized f-mean: (, …,) = (= ()) This covers the geometric mean without using a limit with f(x) = log(x). The power mean is obtained for f(x) = x p. Properties of these means are studied in de Carvalho (2016).

  6. Geometric standard deviation - Wikipedia

    en.wikipedia.org/wiki/Geometric_standard_deviation

    The geometric standard deviation is used as a measure of log-normal dispersion analogously to the geometric mean. [3] As the log-transform of a log-normal distribution results in a normal distribution, we see that the geometric standard deviation is the exponentiated value of the standard deviation of the log-transformed values, i.e. = ⁡ (⁡ (⁡)).

  7. Geometric distribution - Wikipedia

    en.wikipedia.org/wiki/Geometric_distribution

    The geometric distribution is a special case of discrete compound Poisson distribution. [11]: 606 The minimum of geometric random variables with parameters , …, is also geometrically distributed with parameter = (). [15]

  8. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    This estimate is sometimes referred to as the "geometric CV" (GCV), [19] [20] due to its use of the geometric variance. Contrary to the arithmetic standard deviation, the arithmetic coefficient of variation is independent of the arithmetic mean. The parameters μ and σ can be obtained, if the arithmetic mean and the arithmetic variance are known:

  9. Pythagorean means - Wikipedia

    en.wikipedia.org/wiki/Pythagorean_means

    A geometric construction of the quadratic mean and the Pythagorean means (of two numbers a and b). Harmonic mean denoted by H, geometric by G, arithmetic by A and quadratic mean (also known as root mean square) denoted by Q. Comparison of the arithmetic, geometric and harmonic means of a pair of numbers.