Name
Abstract | ||
|---|---|---|
An efficient procedure for the blind inversion of a nonlinear Wiener system is proposed. We show that the problem can be expressed as a problem of blind source separation in nonlinear mixtures for which a solution has been previously proposed. Based on a quasi-nonparametric relative gradient descent, the proposed algorithm can perform efficiently even in the presence of hard distortions |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/78.917796 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
nonlinear mixture,quasi-nonparametric relative gradient descent,efficient procedure,quasi-nonparametric blind inversion,blind inversion,nonlinear wiener system,blind source separation,hard distortion,proposed algorithm,mutual information,monte carlo simulations,mathematical model,identification,nonlinear systems,inverse problems,wiener filter,cost function,gradient descent,nonlinear distortion | Gradient method,Wiener process,Mathematical optimization,Gradient descent,Nonlinear system,Control theory,Deconvolution,Inverse problem,System identification,Blind signal separation,Mathematics | Journal |
Volume | Issue | ISSN |
49 | 5 | 1053-587X |
Citations | PageRank | References |
33 | 2.12 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Taleb | 1 | 232 | 16.71 |
| J. Sole | 2 | 33 | 2.12 |
| Christian Jutten | 3 | 450 | 39.98 |