Abstract

It is known that the discrete Fourier transform (DFT) used in digital signal processing can be characterized in the framework of the representation theory of algebras, namely, as the decomposition matrix for the regular module ${\mathbb{C}}[Z_n] = {\mathbb{C}}[x]/(x^n - 1)$. This characterization provides deep insight into the DFT and can be used to derive and understand the structure of its fast algorithms. In this paper we present an algebraic characterization of the important class of discrete cosine and sine transforms as decomposition matrices of certain regular modules associated with four series of Chebyshev polynomials. Then we derive most of their known algorithms by pure algebraic means. We identify the mathematical principle behind each algorithm and give insight into its structure. Our results show that the connection between algebra and digital signal processing is stronger than previously understood.

MSC codes

  1. 42C05
  2. 42C10
  3. 33C80
  4. 33C90
  5. 65T50
  6. 65T99
  7. 15A23
  8. 62-07

Keywords

  1. discrete cosine transform (DCT)
  2. group representation
  3. symmetry
  4. discrete sine transform (DST)
  5. discrete trigonometric transform (DTT)
  6. discrete Fourier transform (DFT)
  7. FFT
  8. polynomial transform
  9. fast algorithm
  10. Chebyshev polynomial
  11. algebra representation

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Information & Authors

Information

Published In

cover image SIAM Journal on Computing
SIAM Journal on Computing
Pages: 1280 - 1316
ISSN (online): 1095-7111

History

Published online: 17 February 2012

MSC codes

  1. 42C05
  2. 42C10
  3. 33C80
  4. 33C90
  5. 65T50
  6. 65T99
  7. 15A23
  8. 62-07

Keywords

  1. discrete cosine transform (DCT)
  2. group representation
  3. symmetry
  4. discrete sine transform (DST)
  5. discrete trigonometric transform (DTT)
  6. discrete Fourier transform (DFT)
  7. FFT
  8. polynomial transform
  9. fast algorithm
  10. Chebyshev polynomial
  11. algebra representation

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