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A simple approximation for Fast Nonlinear Deconvolution
(Springer, 2011)
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. ...
A simple approximation for fast nonlinear deconvolution
(Springer, 2011-11)
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. ...
A Fast Algorithm For Sparse Multichannel Blind Deconvolution
(SOC EXPLORATION GEOPHYSICISTSTULSA, 2016)
A Fast Algorithm For Sparse Multichannel Blind Deconvolution
(Soc Exploration GeophysicistsTulsa, 2016)
A fast gradient approximation for nonlinear blind signal processing
(Springer, 2013-12)
When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation) complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for ...
Improvement of bioactive metabolite production in microbial cultures—A systems approach by OSMAC and deconvolution-based 1HNMR quantification
(2019-08-01)
Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. Nonetheless, the absence of biotic and abiotic interactions generally observed in nature still limit the chemical diversity ...
Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm
(Brasil, 2013)
This letter presents ACOBBR - V, a new computationally efficient ant-colony-optimization-based algorithm, tailored for continuous-domain problems. The ACOBBR - V algorithm is well suited for application in seismic inversion ...
Sparse Blind Deconvolution Based On Scale Invariant Smoothed 0-norm
(European Signal Processing Conference, EUSIPCO, 2014)
Fast Transforms for Acoustic Imaging-Part I: Theory
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2011)
The classical approach for acoustic imaging consists of beamforming, and produces the source distribution of interest convolved with the array point spread function. This convolution smears the image of interest, significantly ...