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
Link To Document :
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