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Fourier transform
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=== FourierāStieltjes transform on measurable spaces <span class="anchor" id="Fourier-Stieltjes transform"></span>=== {{see also|BochnerāMinlos theorem|RieszāMarkovāKakutani representation theorem|Fourier series#Fourier-Stieltjes series}} The Fourier transform of a [[finite measure|finite]] [[Borel measure]] {{mvar|μ}} on {{math|'''R'''<sup>''n''</sup>}} is given by the continuous function:{{sfn|Pinsky|2002|p=256}} <math display="block">\hat\mu(\xi)=\int_{\mathbb{R}^n} e^{-i 2\pi x \cdot \xi}\,d\mu,</math> and called the ''Fourier-Stieltjes transform'' due to its connection with the [[RiemannāStieltjes integral#Application to functional analysis|Riemann-Stieltjes integral]] representation of [[Radon measure|(Radon) measures]].{{sfn|Edwards|1982|pp=53,67,72-73}} If <math>\mu</math> is the [[probability distribution]] of a [[random variable]] <math>X</math> then its FourierāStieltjes transform is, by definition, a [[Characteristic function (probability theory)|characteristic function]].<ref>{{harvnb|Katznelson|2004|p=173}} {{pb}} The typical conventions in probability theory take {{math|''e''<sup>''iξx''</sup>}} instead of {{math|''e''<sup>ā''i''2Ļ''ξx''</sup>}}.</ref> If, in addition, the probability distribution has a [[probability density function]], this definition is subject to the usual Fourier transform.{{sfn|Billingsley|1995|p=345}} Stated more generally, when <math>\mu</math> is [[Absolute continuity#Absolute continuity of measures|absolutely continuous]] with respect to the Lebesgue measure, i.e., <math display="block"> d\mu = f(x)dx,</math> then <math display="block">\hat{\mu}(\xi)=\hat{f}(\xi),</math> and the Fourier-Stieltjes transform reduces to the usual definition of the Fourier transform. That is, the notable difference with the Fourier transform of integrable functions is that the Fourier-Stieltjes transform need not vanish at infinity, i.e., the [[RiemannāLebesgue lemma]] fails for measures.{{sfn|Katznelson|2004|pp=155,164}} [[Bochner's theorem]] characterizes which functions may arise as the FourierāStieltjes transform of a positive measure on the circle. One example of a finite Borel measure that is not a function is the [[Dirac measure]].{{sfn|Edwards|1982|p=53}} Its Fourier transform is a constant function (whose value depends on the form of the Fourier transform used).
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