Name
Abstract | ||
|---|---|---|
When dealing with nonlinear blind deconvolution, complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing or in microarray data analysis. In this paper we propose a simple method to reduce computational time for the inversion of Wiener systems by using a linear approximation in a minimum-mutual information algorithm. Experimental results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-25020-0_8 | NOLISP |
Keywords | Field | DocType |
simple approximation,fast nonlinear deconvolution,nonlinear blind deconvolution,linear spline interpolation,linear approximation,computational time,wiener system,microarray data analysis,minimum-mutual information algorithm,complex mathematical estimation,good result | Linear approximation,Speech processing,Nonlinear system,Spline interpolation,Blind deconvolution,Computer science,Deconvolution,Algorithm,Mutual information,Nonlinear distortion | Conference |
Volume | ISSN | Citations |
7015 | 0302-9743 | 2 |
PageRank | References | Authors |
0.40 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jordi Solé-Casals | 1 | 82 | 23.24 |
| C. F. Caiafa | 2 | 349 | 15.08 |