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[[File:Sigma-approximation of a Square Wave .gif|thumb|Animation of the additive synthesis of a square wave with an increasing number of harmonics by way of the σ-approximation with p=1]]
In [[mathematics]], '''σ-approximation''' adjusts a [[Fourier series|Fourier summation]] to greatly reduce the [[Gibbs phenomenon]], which would otherwise occur at [[Discontinuity (mathematics)|discontinuities]].<ref>{{Cite journal |last=Chhoa |first=Jannatul Ferdous |date=2020-08-01 |title=An Adaptive Approach to
<math display="block">s(\theta) = \frac{1}{2} a_0 + \sum_{k=1}^{m-1} \left(\operatorname{sinc} \frac{k}{m}\right)^{p} \cdot \left[a_{k} \cos \left( \frac{2 \pi k}{T} \theta \right) + b_k \sin \left( \frac{2 \pi k}{T} \theta \right) \right],</math>
in terms of the normalized [[sinc function]]:
<math display="block"> \operatorname{sinc} x = \frac{\sin \pi x}{\pi x}.</math>
<math> a_{k} </math> and <math> b_{k} </math> are the typical Fourier Series coefficients, and ''p'', a non negative parameter, determines the amount of smoothening applied, where higher values of ''p'' further reduce the Gibbs phenomenon but can overly smoothen the representation of the function.
The term
<math display="block">\left(\operatorname{sinc} \frac{k}{m}\right)^{p}</math>
is the '''Lanczos σ factor''', which is responsible for eliminating most of the Gibbs phenomenon.
As is known by the [[Uncertainty principle]], having a sharp cutoff in the frequency ___domain (cutting off the Fourier Series abruptly without adjusting coefficients) causes a wide spread of information in the time ___domain (lots of ringing).
This can also be understood as applying a [[Window function]] to the Fourier series coefficients to balance maintaining a fast rise time (analogous to a narrow transition band) and small amounts of ringing (analogous to stopband attenuation).
== See also ==
* [[Lanczos resampling]]
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