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Journal ArticleDOI

Eigenvalue and eigenvector decomposition of the discrete Fourier transform

J. McClellan, +1 more
- 01 Mar 1972 - 
- Vol. 20, Iss: 1, pp 66-74
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TLDR
The eigenvalues of a suitably normalized version of the discrete Fourier transform (DFT) are {1, -1,j, -j} and an eigenvector basis is constructed for the DFT.
Abstract
The principal results of this paper are listed as follows. 1) The eigenvalues of a suitably normalized version of the discrete Fourier transform (DFT) are {1, -1,j, -j} . 2) An eigenvector basis is constructed for the DFT. 3) The multiplicities of the eigenvalues are summarized for an N×N transform as follows.

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Citations
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Journal ArticleDOI

The discrete rotational Fourier transform

TL;DR: A discrete version of the angular Fourier transform is defined and the properties of the transform are presented that show it to be a rotation in time-frequency space, this new transform is a generalization of the DFT.
Journal ArticleDOI

Fractional Fourier-Kravchuk transform

TL;DR: In this article, a model of multimodal waveguides with a finite number of sensor points is introduced, and the fractional finite Fourier-Kravchuk transform is defined to self-reproduce these functions.
Journal ArticleDOI

Convergence of iterative nonexpansive signal reconstruction algorithms

TL;DR: In this paper, a general convergence proof for a general class of iterative signal reconstruction algorithms is presented, which relies on the concept of a nonexpansive mapping in both the time and frequency domains.
Journal ArticleDOI

Discrete fractional Hartley and Fourier transforms

TL;DR: In this paper, the eigenvalues and eigenvectors of the discrete Fourier and Hartley transform matrices are investigated, and the results of the eigendecomposition of the transform matrix are used to define DFRHT and DFRFT.
Journal ArticleDOI

The multiple-parameter discrete fractional Fourier transform

TL;DR: The proposed multiple-parameter discrete fractional Fourier transform (MPDFRFT) is shown to have all of the desired properties for fractional transforms and the double random phase encoding in the MPDFRFT domain significantly enhances data security.
References
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Journal ArticleDOI

The finite Fourier transform

TL;DR: In this paper, the finite Fourier transform of a finite sequence is defined and its elementary properties are developed, and the convolution and term-by-term product operations are defined and their equivalent operations in transform space.
Journal ArticleDOI

A short bibliography on the fast Fourier transform

TL;DR: A guided tour of the fast Fourier transform,” IEEE Spectrum (to be published).
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