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{{confusing|date=May 2010}}
In [[mathematical analysis]], the '''Dirichlet kernel''' is the collection of functions
 
:<math>D_n(x)=\sum_{k=-n}^n
e^{ikx}=1+2\sum_{k=1}^n\cos(kx)=\frac{\sin\left(\left(n +1/2\right) x \right)}{\sin(x/2)}.</math>
 
It is named after [[Peter Gustav Lejeune Dirichlet]].
 
The importance of the Dirichlet kernel comes from its relation to [[Fourier series]]. The [[convolution]] of ''D<sub>n</sub>''(''x'') with any function ''f'' of period 2π is the ''n''th-degree Fourier series approximation to ''f'', i.e., we have
 
:<math>(D_n*f)(x)=\frac{1}{2\pi}\int_{-\pi}^\pi f(y)D_n(x-y)\,dy=\sum_{k=-n}^n \hat{f}(k)e^{ikx},</math>
 
where
 
:<math>\hat{f}(k)=\frac{1}{2\pi}\int_{-\pi}^\pi f(x)e^{-ikx}\,dx</math>
 
is the ''k''th Fourier coefficient of ''f''. This implies that in order to study convergence of Fourier series it is enough to study properties of the Dirichlet kernel. Of particular importance is the fact that the [[Lp space|''L''<sup>1</sup>]] norm of ''D<sub>n</sub>'' diverges to infinity as ''n'' → ∞. One can estimate that
 
:<math>\| D_n \| _{L^1} \approx \log n</math>
 
where <math>\approx</math> denotes "is of the order." This lack of uniform integrability is behind many divergence phenomena for the Fourier series. For example, together with the [[uniform boundedness principle]], it can be used to show that the Fourier series of a [[continuous function]] may fail to converge pointwise, in rather dramatic fashion. See [[convergence of Fourier series]] for further details.
 
[[File:Dirichlet.png|thumb|400px|Plot of the first few Dirichlet kernels]]
 
==Relation to the delta function==
<!--I am not sure this is useful here.
 
To understand the definition, one can see that it is 2&pi; times the ''n''th-degree Fourier series approximation to a "function" with period 2&pi; given by
 
:<math>\delta_p(x)=\sum_{k=-\infty}^\infty\delta(x-2\pi k)</math>
where &delta;-->
 
Take the [[periodic function|periodic]] [[Dirac delta function]], which is not really a function, in the sense of mapping one set into another, but is rather a "[[generalized function]]", also called a "distribution", and multiply by 2π. We get the [[identity element]] for convolution on functions of period 2π. In other words, we have
 
:<math>f*(2\pi \delta)=f \,</math>
 
for every function ''f'' of period 2π. The Fourier series representation of this "function" is
 
:<math>2\pi \delta(x)\sim\sum_{k=-\infty}^\infty e^{ikx}=\left(1 +2\sum_{k=1}^\infty\cos(kx)\right).</math>
 
Therefore the Dirichlet kernel, which is just the sequence of partial sums of this series, can be thought of as an ''[[approximate identity]]''. Abstractly speaking it is not however an approximate identity of ''positive'' elements (hence the failures mentioned above).
 
==Proof of the trigonometric identity==
 
The [[trigonometric identity]]
 
:<math>\sum_{k=-n}^n e^{ikx}
=\frac{\sin((n+1/2)x)}{\sin(x/2)}</math>
 
displayed at the top of this article may be established as follows.  First recall that the sum of a finite [[geometric series]] is
 
:<math>\sum_{k=0}^n a r^k=a\frac{1-r^{n+1}}{1-r}.</math>
 
In particular, we have
 
:<math>\sum_{k=-n}^n r^k=r^{-n}\cdot\frac{1-r^{2n+1}}{1-r}.</math>
 
Multiply both the numerator and the denominator by ''r''<sup>&minus;1/2</sup>, getting
 
:<math>\frac{r^{-n-1/2}}{r^{-1/2}}\cdot\frac{1-r^{2n+1}}{1-r} =\frac{r^{-n-1/2}-r^{n+1/2}}{r^{-1/2}-r^{1/2}}.</math>
 
In the case ''r'' = ''e''<sup>''ix''</sup> we have
 
:<math>\sum_{k=-n}^n e^{ikx}=\frac{e^{-(n+1/2)ix}-e^{(n+1/2)ix}}{e^{-ix/2}-e^{ix/2}} =\frac{-2i\sin((n+1/2)x)}{-2i\sin(x/2)} = \frac{\sin((n+1/2)x)}{\sin(x/2)}</math>
 
as required.
 
===Alternative proof of the trigonometric identity===
 
Start with the series
 
:<math>f(x) = 1/2 + \sum_{k=1}^n\cos(kx).</math>
 
Multiply both sides of the above by
 
:<math>2\sin(x/2)\!</math>
 
and use the trigonometric identity
 
:<math>\cos(a)\sin(b) = (\sin(a + b) - \sin(a - b))/2\!</math>
 
to reduce the r.h.s. to
 
:<math>\sin((n + 1/2)x).\!</math>
 
== Variant of identity ==
If the sum is only over positive integers (which may arise when computing a DFT that is not centered), then using similar techniques we can show the following identity:
:<math>\sum_{k=0}^n e^{ikx}
=e^{ixn/2}\frac{\sin((n/2+1/2)x)}{\sin(x/2)}</math>
 
==References==
* Andrew M. Bruckner, Judith B. Bruckner, Brian S. Thomson: ''Real Analysis''. ClassicalRealAnalysis.com 1996, ISBN 0-13-458886-X, S.620 ([http://books.google.de/books?id=1WY6u0C_jEsC vollständige Online-Version (Google Books)])
* {{springer|title=Dirichlet kernel|id=p/d032880}}
* [http://planetmath.org/encyclopedia/DirichletKernel.html Dirichlet-Kernel at [[PlanetMath]]]
 
[[Category:Mathematical analysis]]
[[Category:Fourier series]]
[[Category:Approximation theory]]
[[Category:Articles containing proofs]]

Revision as of 04:28, 8 March 2013

I'm Robin and was born on 14 August 1971. My hobbies are Disc golf and Hooping.

My web site - http://www.hostgator1centcoupon.info/ In mathematical analysis, the Dirichlet kernel is the collection of functions

It is named after Peter Gustav Lejeune Dirichlet.

The importance of the Dirichlet kernel comes from its relation to Fourier series. The convolution of Dn(x) with any function f of period 2π is the nth-degree Fourier series approximation to f, i.e., we have

where

is the kth Fourier coefficient of f. This implies that in order to study convergence of Fourier series it is enough to study properties of the Dirichlet kernel. Of particular importance is the fact that the L1 norm of Dn diverges to infinity as n → ∞. One can estimate that

where denotes "is of the order." This lack of uniform integrability is behind many divergence phenomena for the Fourier series. For example, together with the uniform boundedness principle, it can be used to show that the Fourier series of a continuous function may fail to converge pointwise, in rather dramatic fashion. See convergence of Fourier series for further details.

Plot of the first few Dirichlet kernels

Relation to the delta function

Take the periodic Dirac delta function, which is not really a function, in the sense of mapping one set into another, but is rather a "generalized function", also called a "distribution", and multiply by 2π. We get the identity element for convolution on functions of period 2π. In other words, we have

for every function f of period 2π. The Fourier series representation of this "function" is

Therefore the Dirichlet kernel, which is just the sequence of partial sums of this series, can be thought of as an approximate identity. Abstractly speaking it is not however an approximate identity of positive elements (hence the failures mentioned above).

Proof of the trigonometric identity

The trigonometric identity

displayed at the top of this article may be established as follows. First recall that the sum of a finite geometric series is

In particular, we have

Multiply both the numerator and the denominator by r−1/2, getting

In the case r = eix we have

as required.

Alternative proof of the trigonometric identity

Start with the series

Multiply both sides of the above by

and use the trigonometric identity

to reduce the r.h.s. to

Variant of identity

If the sum is only over positive integers (which may arise when computing a DFT that is not centered), then using similar techniques we can show the following identity:

References