Fejér kernel

Plot of several Fejér kernels

In mathematics, the Fejér kernel is a summability kernel used to express the effect of Cesàro summation on Fourier series. It is a non-negative kernel, giving rise to an approximate identity. It is named after the Hungarian mathematician Lipót Fejér (1880–1959).

Definition

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The Fejér kernel has many equivalent definitions. Three such definitions are outlined below:

1) The traditional definition expresses the Fejér kernel in terms of the Dirichlet kernel

where

is the th order Dirichlet kernel.

2) The Fejér kernel may also be written in a closed form expression as follows[1]

This closed form expression may be derived from the definitions used above. A proof of this result goes as follows.

Using the fact that the Dirichlet kernel may be written as:[2]

,

one obtains from the definition of the Fejér kernel above:

By the trigonometric identity: , one has

which allows evaluation of as a telescoping sum:

3) The Fejér kernel can also be expressed as:

Properties

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The Fejér kernel is a positive summability kernel. An important property of the Fejér kernel is with average value of .

Convolution

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The convolution is positive: for of period it satisfies

Since

we have

which is Cesàro summation of Fourier series. By Young's convolution inequality,

Additionally, if , then

a.e.

Since is finite, , so the result holds for other spaces, as well.

If is continuous, then the convergence is uniform, yielding a proof of the Weierstrass theorem.

  • One consequence of the pointwise a.e. convergence is the uniqueness of Fourier coefficients: If with , then a.e. This follows from writing

which depends only on the Fourier coefficients.

  • A second consequence is that if exists a.e., then a.e., since Cesàro means converge to the original sequence limit if it exists.

Applications

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The Fejér kernel is used in signal processing and Fourier analysis.

See also

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References

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  1. ^ Hoffman, Kenneth (1988). Banach Spaces of Analytic Functions. Dover. p. 17. ISBN 0-486-45874-1.
  2. ^ Königsberger, Konrad. Analysis 1 (in German) (6th ed.). Springer. p. 322.