特征向量的DFT和基于双线性变换的离散分数傅里叶变换

A. Serbes, L. D. Ata
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引用次数: 1

摘要

DFT矩阵的正交特征向量更接近于厄米-高斯函数的样本,是定义离散分数阶傅里叶变换的关键。在这项工作中,我们确定了由双线性变换启发的DFT矩阵的特征向量。双线性变换将模拟空间映射到离散样本,并将模拟s域中的jw映射到离散z域中的单位圆上,没有混叠,因此适合用于傅里叶变换的特征函数的离散化。我们得到了DFT矩阵的类厄米高斯特征向量,并通过大量的仿真验证了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eigenvectors of the DFT and discrete fractional fourier transform based on the bilinear transform
Orthonormal eigenvectors of the DFT matrix, which is closer to the samples of Hermite-Gaussian functions, are crucial to define the discrete fractional Fourier transform. In this work we determine the eigenvectors of the DFT matrix inspired by the bilinear transform. The bilinear transform maps the analog space to the discrete sample and it maps jw in the analog s-domain to the unit circle in the discrete z-domain one-to-one without aliasing, it is appropriate to use in the discretization of the eigenfunctions of the Fourier transform. We obtain Hermite-Gaussian like eigenvectors of the DFT matrix and confirm the results with extensive simulations.
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