Eigenvectors of the Discrete Fourier Transform Based on the Bilinear Transform

Determining orthonormal eigenvectors of the DFT matrix, which is closer to the samples of Hermite-Gaussian functions, is crucial in the definition of the discrete fractional Fourier transform. In this work, we disclose eigenvectors of the DFT matrix inspired by the ideas behind bilinear transform. The bilinear transform maps the analog space to the discrete sample space. As j in the analog s-domain is mapped to the unit circle one-to-one without aliasing in the discrete z-domain, it is appropriate to use it in the discretization of the eigenfunctions of the Fourier transform. We obtain Hermite-Gaussian-like eigenvectors of the DFT matrix. For this purpose we propose three different methods and analyze their stability conditions. These methods include better conditioned commuting matrices and higher order methods. We confirm the results with extensive simulations.

[1]  Balu Santhanam,et al.  Discrete Gauss-Hermite Functions and Eigenvectors of the Centered Discrete Fourier Transform , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[2]  Levent Onural,et al.  Optimal filtering in fractional Fourier domains , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[3]  Z. Zalevsky,et al.  The Fractional Fourier Transform: with Applications in Optics and Signal Processing , 2001 .

[4]  James H. McClellan,et al.  The discrete rotational Fourier transform , 1996, IEEE Trans. Signal Process..

[5]  F. Grünbaum,et al.  The eigenvectors of the discrete Fourier transform: A version of the Hermite functions , 1982 .

[6]  Xiang-Gen Xia,et al.  On bandlimited signals with fractional Fourier transform , 1996, IEEE Signal Processing Letters.

[7]  Cagatay Candan,et al.  The discrete fractional Fourier transform , 2000, IEEE Trans. Signal Process..

[8]  Soo-Chang Pei,et al.  Discrete Fractional Fourier Transform Based on New Nearly Tridiagonal Commuting Matrices , 2006, IEEE Trans. Signal Process..

[9]  Soo-Chang Pei,et al.  Generalized Commuting Matrices and Their Eigenvectors for DFTs, Offset DFTs, and Other Periodic Operations , 2008, IEEE Transactions on Signal Processing.

[10]  Cagatay Candan,et al.  On Higher Order Approximations for Hermite–Gaussian Functions and Discrete Fractional Fourier Transforms , 2007, IEEE Signal Processing Letters.

[11]  B. Dickinson,et al.  Eigenvectors and functions of the discrete Fourier transform , 1982 .

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  Soo-Chang Pei,et al.  DFT-Commuting Matrix With Arbitrary or Infinite Order Second Derivative Approximation , 2009, IEEE Transactions on Signal Processing.

[14]  Charles Audet,et al.  Analysis of Generalized Pattern Searches , 2000, SIAM J. Optim..

[15]  Olcay Akay,et al.  Fractional convolution and correlation via operator methods and an application to detection of linear FM signals , 2001, IEEE Trans. Signal Process..

[16]  Lutfiye Durak-Ata,et al.  Efficient computation of DFT commuting matrices by a closed-form infinite order approximation to the second differentiation matrix , 2011, Signal Processing.

[17]  Gene H. Golub,et al.  Matrix computations , 1983 .

[18]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .