• DocumentCode
    1099902
  • Title

    Algebraic Signal Processing Theory: Cooley–Tukey Type Algorithms for DCTs and DSTs

  • Author

    Püschel, Markus ; Moura, José M F

  • Author_Institution
    Carnegie Mellon Univ., Pittsburgh
  • Volume
    56
  • Issue
    4
  • fYear
    2008
  • fDate
    4/1/2008 12:00:00 AM
  • Firstpage
    1502
  • Lastpage
    1521
  • Abstract
    This paper presents a systematic methodology to derive and classify fast algorithms for linear transforms. The approach is based on the algebraic signal processing theory. This means that the algorithms are not derived by manipulating the entries of transform matrices, but by a stepwise decomposition of the associated signal models, or polynomial algebras. This decomposition is based on two generic methods or algebraic principles that generalize the well-known Cooley-Tukey fast Fourier transform (FFT) and make the algorithms´ derivations concise and transparent. Application to the 16 discrete cosine and sine transforms yields a large class of fast general radix algorithms, many of which have not been found before.
  • Keywords
    discrete cosine transforms; fast Fourier transforms; polynomial matrices; signal processing; Cooley-Tukey fast Fourier transform; DCT; DST; algebraic signal processing theory; discrete cosine transform; discrete sine transform; linear transform; polynomial algebra; transform matrices; Algebra; Application specific processors; Discrete Fourier transforms; Discrete cosine transforms; Discrete transforms; Fast Fourier transforms; Filters; Fourier transforms; Polynomials; Signal processing algorithms; Chinese remainder theorem; discrete Fourier transform (DFT); discrete cosine transform (DCT); discrete sine transform (DST); fast Fourier transform (FFT); polynomial algebra; representation theory;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2007.907919
  • Filename
    4471889