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An Algorithm for Computing DFT Using Arithmetic Fourier Transform
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TLDR
A new Fourier analysis technique called the arithmetic Fourier transform (AFT) is used to compute DFT, which needs only O(N) multiplications and opens up a new approach for the fast computation of DFT.Abstract:
The Discrete Fourier Transform (DFT) plays an important role in digital signal processing and many other fields.In this paper,a new Fourier analysis technique called the arithmetic Fourier transform (AFT) is used to compute DFT.This algorithm needs only O(N) multiplications.The process of the algorithm is simple and it has a unified formula,which overcomes the disadvantage of the traditional fast method that has a complex program containing too many subroutines.The algorithm can be easily performed in parallel,especially suitable for VLSI designing.For a DFT at a length that contains big prime factors,especially for a DFT at a prime length,it is faster than the traditional FFT method.The algorithm opens up a new approach for the fast computation of DFT.read more
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Book ChapterDOI
Harmonic Analyzing Based on Cubic Spline Interpolated Arithmetic Fourier Transform
TL;DR: The cubic spline interpolation is selected to improve the accuracy due to its higher precision and better stability and the MATLAB simulation results show that the new interpolation can meet the requirements of power system harmonic analysis, make AFT better computational characteristics, and provide new ways for harmonic analysis.
Proceedings ArticleDOI
Study of brainwave frequency spectrum by AFT and FFT
TL;DR: A new Fourier analysis technique caller arithmetic Fourier transform (AFT) is presented in this paper that overcomes the disadvantage of the traditional FFT and improves speed and accuracy of the calculation.