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
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