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If f is a Schwartz function, then τ x f is the convolution with a translated Dirac delta function τ x f = f ∗ τ x δ. So translation invariance of the convolution of Schwartz functions is a consequence of the associativity of convolution. Furthermore, under certain conditions, convolution is the most general translation invariant operation.
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.
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).
Animation of how cross-correlation is calculated. The left graph shows a green function G that is phase-shifted relative to function F by a time displacement of 𝜏. The middle graph shows the function F and the phase-shifted G represented together as a Lissajous curve. Integrating F multiplied by the phase-shifted G produces the right graph ...
This definition makes sense if x is an integrable function (in L 1), a rapidly decreasing distribution (in particular, a compactly supported distribution) or is a finite Borel measure. 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 ...
Mathematically, a moving average is a type of convolution. Thus in signal processing it is viewed as a low-pass finite impulse response filter. Because the boxcar function outlines its filter coefficients, it is called a boxcar filter. It is sometimes followed by downsampling.
This is consistent with the characteristic function of being a Wick rotation of () when the moment generating function exists, as the characteristic function of a continuous random variable is the Fourier transform of its probability density function (), and in general when a function () is of exponential order, the Fourier transform of is a ...
The pseudo-Voigt profile (or pseudo-Voigt function) is an approximation of the Voigt profile V(x) using a linear combination of a Gaussian curve G(x) and a Lorentzian curve L(x) instead of their convolution. The pseudo-Voigt function is often used for calculations of experimental spectral line shapes.