Name
Abstract | ||
|---|---|---|
In our paper titled ldquoalgebraic signal processing theory: foundation and 1-D Timerdquo appearing in this issue of the IEEE Transactions on Signal Processing, we presented the algebraic signal processing theory, an axiomatic and general framework for linear signal processing. The basic concept in this theory is the signal model defined as the triple (A,M,Phi), where A is a chosen algebra of filters, M an associated A-module of signals, and Phi is a generalization of the z-transform. Each signal model has its own associated set of basic SP concepts, including filtering, spectrum, and Fourier transform. Examples include infinite and finite discrete time where these notions take their well-known forms. In this paper, we use the algebraic theory to develop infinite and finite space signal models. These models are based on a symmetric space shift operator, which is distinct from the standard time shift. We present the space signal processing concepts of filtering or convolution, ldquoz -transform,rdquo spectrum, and Fourier transform. For finite length space signals, we obtain 16 variants of space models, which have the 16 discrete cosine and sine transforms (DCTs/DSTs) as Fourier transforms. Using this novel derivation, we provide missing signal processing concepts associated with the DCTs/DSTs, establish them as precise analogs to the DFT, get deep insight into their origin, and enable the easy derivation of many of their properties including their fast algorithms. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TSP.2008.925259 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
space signal processing concept,algebraic signal processing theory,finite length space signal,missing signal processing concept,symmetric space shift operator,finite space signal model,space model,1-d space,signal model,linear signal processing,ldquoalgebraic signal processing theory,shift operator,boundary condition,spectrum,module,dft,fourier transform,signal processing,discrete time,discrete cosine transform,convolution,algebra,chebyshev polynomials,discrete sine transform,symmetric space,filtering,dst,dct,chebyshev polynomial,fourier transforms,polynomials,representation theory | Signal processing,Digital signal processing,Multidimensional signal processing,Algebra,Convolution,Filter (signal processing),Discrete sine transform,Algebraic signal processing,Mathematics,Signal reconstruction | Journal |
Volume | Issue | ISSN |
56 | 8 | 1053-587X |
Citations | PageRank | References |
38 | 2.64 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Markus Püschel | 1 | 223 | 24.30 |
| José M. F. Moura | 2 | 5137 | 426.14 |