A simple approximation for fast nonlinear deconvolution

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

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. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Solé-Casals, J., & Caiafa, C. F. (2011). A simple approximation for fast nonlinear deconvolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7015 LNAI, pp. 55–62). https://doi.org/10.1007/978-3-642-25020-0_8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free