Summability kernel

Family of functions

In mathematics, a summability kernel is a family or sequence of periodic integrable functions satisfying a certain set of properties, listed below. Certain kernels, such as the Fejér kernel, are particularly useful in Fourier analysis. Summability kernels are related to approximation of the identity; definitions of an approximation of identity vary,[1] but sometimes the definition of an approximation of the identity is taken to be the same as for a summability kernel.

Definition

Let T := R / Z {\displaystyle \mathbb {T} :=\mathbb {R} /\mathbb {Z} } . A summability kernel is a sequence ( k n ) {\displaystyle (k_{n})} in L 1 ( T ) {\displaystyle L^{1}(\mathbb {T} )} that satisfies

  1. T k n ( t ) d t = 1 {\displaystyle \int _{\mathbb {T} }k_{n}(t)\,dt=1}
  2. T | k n ( t ) | d t M {\displaystyle \int _{\mathbb {T} }|k_{n}(t)|\,dt\leq M} (uniformly bounded)
  3. δ | t | 1 2 | k n ( t ) | d t 0 {\displaystyle \int _{\delta \leq |t|\leq {\frac {1}{2}}}|k_{n}(t)|\,dt\to 0} as n {\displaystyle n\to \infty } , for every δ > 0 {\displaystyle \delta >0} .

Note that if k n 0 {\displaystyle k_{n}\geq 0} for all n {\displaystyle n} , i.e. ( k n ) {\displaystyle (k_{n})} is a positive summability kernel, then the second requirement follows automatically from the first.

With the more usual convention T = R / 2 π Z {\displaystyle \mathbb {T} =\mathbb {R} /2\pi \mathbb {Z} } , the first equation becomes 1 2 π T k n ( t ) d t = 1 {\displaystyle {\frac {1}{2\pi }}\int _{\mathbb {T} }k_{n}(t)\,dt=1} , and the upper limit of integration on the third equation should be extended to π {\displaystyle \pi } , so that the condition 3 above should be

δ | t | π | k n ( t ) | d t 0 {\displaystyle \int _{\delta \leq |t|\leq \pi }|k_{n}(t)|\,dt\to 0} as n {\displaystyle n\to \infty } , for every δ > 0 {\displaystyle \delta >0} .

This expresses the fact that the mass concentrates around the origin as n {\displaystyle n} increases.

One can also consider R {\displaystyle \mathbb {R} } rather than T {\displaystyle \mathbb {T} } ; then (1) and (2) are integrated over R {\displaystyle \mathbb {R} } , and (3) over | t | > δ {\displaystyle |t|>\delta } .

Examples

  • The Fejér kernel
  • The Poisson kernel (continuous index)
  • The Landau kernel
  • The Dirichlet kernel is not a summability kernel, since it fails the second requirement.

Convolutions

Let ( k n ) {\displaystyle (k_{n})} be a summability kernel, and {\displaystyle *} denote the convolution operation.

  • If ( k n ) , f C ( T ) {\displaystyle (k_{n}),f\in {\mathcal {C}}(\mathbb {T} )} (continuous functions on T {\displaystyle \mathbb {T} } ), then k n f f {\displaystyle k_{n}*f\to f} in C ( T ) {\displaystyle {\mathcal {C}}(\mathbb {T} )} , i.e. uniformly, as n {\displaystyle n\to \infty } . In the case of the Fejer kernel this is known as Fejér's theorem.
  • If ( k n ) , f L 1 ( T ) {\displaystyle (k_{n}),f\in L^{1}(\mathbb {T} )} , then k n f f {\displaystyle k_{n}*f\to f} in L 1 ( T ) {\displaystyle L^{1}(\mathbb {T} )} , as n {\displaystyle n\to \infty } .
  • If ( k n ) {\displaystyle (k_{n})} is radially decreasing symmetric and f L 1 ( T ) {\displaystyle f\in L^{1}(\mathbb {T} )} , then k n f f {\displaystyle k_{n}*f\to f} pointwise a.e., as n {\displaystyle n\to \infty } . This uses the Hardy–Littlewood maximal function. If ( k n ) {\displaystyle (k_{n})} is not radially decreasing symmetric, but the decreasing symmetrization k ~ n ( x ) := sup | y | | x | k n ( y ) {\displaystyle {\widetilde {k}}_{n}(x):=\sup _{|y|\geq |x|}k_{n}(y)} satisfies sup n N k ~ n 1 < {\displaystyle \sup _{n\in \mathbb {N} }\|{\widetilde {k}}_{n}\|_{1}<\infty } , then a.e. convergence still holds, using a similar argument.

References

  1. ^ Pereyra, María; Ward, Lesley (2012). Harmonic Analysis: From Fourier to Wavelets. American Mathematical Society. p. 90.
  • Katznelson, Yitzhak (2004), An introduction to Harmonic Analysis, Cambridge University Press, ISBN 0-521-54359-2