• DocumentCode
    2964124
  • Title

    Algebraic Signal Processing Theory: An Overview

  • Author

    Püschel, Markus

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA
  • fYear
    2006
  • fDate
    24-27 Sept. 2006
  • Firstpage
    386
  • Lastpage
    391
  • Abstract
    We give an overview of the algebraic signal processing theory, a recently proposed generalization of linear signal processing (SP). Algebraic SP (ASP) is built axiomatically on top of the concept of a signal model, which is a triple (A, M, Phi), where A is a chosen algebra of filters, M an associated A-module of signals, and Phi generalizes the idea of a z-transform. ASP encompasses standard time SP (continuous and discrete, infinite and finite duration), but goes beyond it, for example, by defining meaningful notions of space SP in one and higher dimensions, separable and non-separable. ASP identifies many known transforms as Fourier transforms for a suitably chosen signal model and provides the means to derive and explain existing and novel transform algorithms. As one example, the discrete cosine transform is in ASP the Fourier transform for the finite space model and possesses general radix Cooley-Tukey type algorithms derived by the theory
  • Keywords
    Fourier transforms; algebra; filtering theory; signal processing; ASP; Fourier transform; algebraic signal processing theory; linear signal processing; z-transform; Algebra; Application specific processors; Discrete Fourier transforms; Fast Fourier transforms; Fourier transforms; Mathematics; Nonlinear filters; Signal processing; Signal processing algorithms; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing Workshop, 12th - Signal Processing Education Workshop, 4th
  • Conference_Location
    Teton National Park, WY
  • Print_ISBN
    1-4244-3534-3
  • Electronic_ISBN
    1-4244-0535-1
  • Type

    conf

  • DOI
    10.1109/DSPWS.2006.265417
  • Filename
    4041094