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Gaussian kernel : ウィキペディア英語版
Gaussian function

In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the form:
:f\left(x\right) = a \exp } \right)}
for arbitrary real constants , and . It is named after the mathematician Carl Friedrich Gauss.
The graph of a Gaussian is a characteristic symmetric "bell curve" shape. The parameter is the height of the curve's peak, is the position of the center of the peak and (the standard deviation, sometimes called the Gaussian RMS width) controls the width of the "bell".
Gaussian functions are widely used in statistics where they describe the normal distributions, in signal processing where they serve to define Gaussian filters, in image processing where two-dimensional Gaussians are used for Gaussian blurs, and in mathematics where they are used to solve heat equations and diffusion equations and to define the Weierstrass transform.
==Properties==
Gaussian functions arise by composing the exponential function with a concave quadratic function. The Gaussian functions are thus those functions whose logarithm is a concave quadratic function.
The parameter is related to the full width at half maximum (FWHM) of the peak according to
: \mathrm = 2 \sqrt\ c \approx 2.35482 c.〔Using the logarithmic identity \log \left( x \right) = -\log \left( \frac \right), this expression can be transformed to \mathrm = 2 \sqrt\ c.〕
Alternatively, the parameter can be interpreted by saying that the two inflection points of the function occur at and .
The ''full width at tenth of maximum'' (FWTM) for a Gaussian could be of interest and is
: \mathrm = 2 \sqrt\ c \approx 4.29193 c.〔Using the logarithmic identity \log \left( x \right) = -\log \left( \frac \right), this expression can be transformed to \mathrm = 2 \sqrt\ c.〕
Gaussian functions are analytic, and their limit as is 0 (for the above case of ).
Gaussian functions are among those functions that are elementary but lack elementary antiderivatives; the integral of the Gaussian function is the error function. Nonetheless their improper integrals over the whole real line can be evaluated exactly, using the Gaussian integral
:\int_^\infty e^\,dx=\sqrt
and one obtains
:\int_^\infty a e^\,dx=ac\cdot\sqrt.
This integral is 1 if and only if a = \tfrac\left(\frac\right)^2 }.
These Gaussians are plotted in the accompanying figure.
Gaussian functions centered at zero minimize the Fourier uncertainty principle.
The product of two Gaussian functions is a Gaussian, and the convolution of two Gaussian functions is also a Gaussian, with variance being the sum of the original variances: c^2 = c_^2 + c_^2. The product of two Gaussian probability density functions, though, is not in general a Gaussian PDF.
Taking the Fourier transform (unitary, angular frequency convention) of a Gaussian function with parameters , and yields another Gaussian function, with parameters \sqrtac, and \frac. So in particular the Gaussian functions with and c = \frac}\exp\left(-\pi\cdot\left(\frac\right)^2\right) = c\cdot\sum_{k\in\mathbb{Z}}\exp(-\pi\cdot(kc)^2).

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
ウィキペディアで「Gaussian function」の詳細全文を読む



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