Name
Title | ||
|---|---|---|
Signal Reconstruction From Multiple Unregistered Sets Of Samples Using Groebner Bases |
Abstract | ||
|---|---|---|
We present a new method for signal reconstruction from multiple sets of samples with unknown offsets. We rewrite the reconstruction problem as a set of polynomial equations in the unknown signal parameters and the offsets between the sets of samples. Then, we construct a Grobner basis for the corresponding affine variety. The signal parameters can then easily be derived from this Grobner basis. This provides us with an elegant solution method for the initial nonlinear problem. We show two examples for the reconstruction of polynomial signals and Fourier series. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660726 | 2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13 |
Keywords | Field | DocType |
image reconstruction,grobner basis,groebner basis,aliasing,polynomials,geometry,nonlinear equations,image resolution,signal reconstruction,fourier series | Nonlinear system,Polynomial,Affine variety,Computer science,Artificial intelligence,Gröbner basis,Iterative reconstruction,Pattern recognition,Algebra,Algorithm,Fourier series,Aliasing,Signal reconstruction | Conference |
ISSN | Citations | PageRank |
1520-6149 | 2 | 0.44 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Vandewalle | 1 | 284 | 20.24 |
| Luciano Sbaiz | 2 | 84 | 11.42 |
| Martin Vetterli | 3 | 13926 | 2397.68 |