Title :
A note on the computational complexity of the arithmetic Fourier transform
Author :
Tepedelenlioglu, Nazif
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Inst. of Technol., Melbourne, FL, USA
fDate :
7/1/1989 12:00:00 AM
Abstract :
It is shown that the number of data points the arithmetic Fourier transform (AFT) needs for an N-point Fourier transform is proportional to N2. Thus, for example, while a standard fast Fourier transform algorithm requires 1024 samples to yield 1024 spectral components, AFT would take more than 300000 samples to do the same job
Keywords :
Fourier transforms; computational complexity; spectral analysis; arithmetic Fourier transform; computational complexity; data points; fast Fourier transform; spectral analysis; spectral components; Acoustic signal processing; Acoustic testing; Arithmetic; Computational complexity; Direction of arrival estimation; Fourier transforms; Signal processing; Smoothing methods; Speech; Transmission line matrix methods;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
