• DocumentCode
    1177356
  • 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
  • Volume
    37
  • Issue
    7
  • fYear
    1989
  • fDate
    7/1/1989 12:00:00 AM
  • Firstpage
    1146
  • Lastpage
    1147
  • 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;
  • fLanguage
    English
  • Journal_Title
    Acoustics, Speech and Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0096-3518
  • Type

    jour

  • DOI
    10.1109/29.32291
  • Filename
    32291
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1177356