• DocumentCode
    1287174
  • Title

    Split manageable efficient algorithm for Fourier and Hadamard transforms

  • Author

    Grigoryan, Artyom M. ; Agaian, Sos S.

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    48
  • Issue
    1
  • fYear
    2000
  • fDate
    1/1/2000 12:00:00 AM
  • Firstpage
    172
  • Lastpage
    183
  • Abstract
    In this paper, a general, efficient, manageable split algorithm to compute one-dimensional (1-D) unitary transforms, by using the special partitioning in the frequency domain, is introduced. The partitions determine fast transformations that split the N-point unitary transform into a set of Ni-point transforms i=1: n(N1+...N n=N). Here, we introduce a class of splitting transformations: the so-called paired transforms. Based on these transforms, the decompositions of the Fourier transforms of arbitrary orders are given, and the corresponding algorithms are considered. Comparative estimates revealing the efficiency of the proposed algorithms with respect to the known ones are given. In particular, a proposed method of calculating the 2r-point Fourier transform requires 2r-1(r-3)+2 multiplications and 2r-1(r+9)-r2-3r-6 additions. In terms of the paired transforms, the splitting of the 2r-point Hadamard transform is described. As a result, the proposed algorithm for computing this transform uses on the average no more than six operations of additions per sample
  • Keywords
    Hadamard transforms; discrete Fourier transforms; frequency-domain analysis; signal processing; 1-D unitary transforms; Fourier transforms; Hadamard transforms; N-point unitary transform; additions; efficiency; fast transformations; frequency domain; manageable split algorithm; multiplications; one-dimensional unitary transform; paired transforms; split manageable efficient algorithm; splitting transformations; Algorithm design and analysis; Convolution; Data compression; Discrete Fourier transforms; Fast Fourier transforms; Fourier transforms; Frequency domain analysis; Image processing; Partitioning algorithms; Signal processing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.815487
  • Filename
    815487