In other words, the Hermite functions form a complete orthonormal system of eigenfunctions for the Fourier transform on.
2.
The Hermite functions are thus an orthonormal basis of which " diagonalizes the Fourier transform operator ".
3.
This formula can be used in connection with the recurrence relations for and to calculate any derivative of the Hermite functions efficiently.
4.
Indeed, such an inequality can be checked for creation and annihilation operators acting on Hermite functions " H " " n " and this implies the general inequality.
5.
In Gaussian _ function it says " Mathematically, the derivatives of the Gaussian function are the Hermite functions ", but it seems like the actual derivative is the inverse of a Hermite function.
6.
In Gaussian _ function it says " Mathematically, the derivatives of the Gaussian function are the Hermite functions ", but it seems like the actual derivative is the inverse of a Hermite function.
7.
Since the complete set of Hermite functions provides a resolution of the identity, the Fourier transform can be represented by such a sum of terms weighted by the above eigenvalues, and these sums can be explicitly summed.
8.
An equivalent formulation of the fact that Hermite polynomials are an orthogonal basis for consists in introducing Hermite " functions " ( see below ), and in saying that the Hermite functions are an orthonormal basis for.
9.
Among other properties, Hermite functions decrease exponentially fast in both frequency and time domains, and they are thus used to define a generalization of the Fourier transform, namely the fractional Fourier transform used in time-frequency analysis.
10.
For the continuous Fourier transform, the natural orthogonal eigenfunctions are the Hermite functions, so various discrete analogues of these have been employed as the eigenvectors of the DFT, such as the Kravchuk polynomials ( Atakishiyev and Wolf, 1997 ).
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