Design of Smart Ion-Selective Electrode Arrays Based on Source Separation through Nonlinear Independent Component Analysis
The development of chemical sensor arrays based on Blind Source Separation (BSS) provides a promising solution to overcome the interference problem associated with Ion-Selective Electrodes (ISE). The main motivation behind this new approach is to ease the time-...
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Online Access: | http://dx.doi.org/10.2516/ogst/2013194 |
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doaj-287f1bcbbf9e4a4ebbb4bd1f66d761192021-02-02T06:29:22ZengEDP SciencesOil & Gas Science and Technology1294-44751953-81892014-03-0169229330610.2516/ogst/2013194ogst130105Design of Smart Ion-Selective Electrode Arrays Based on Source Separation through Nonlinear Independent Component AnalysisDuarte L.T.0Jutten C.1School of Applied Sciences, University of Campinas (UNICAMP)GIPSA-lab, UMR 5216 CNRS, Institut Polytechnique de Grenoble The development of chemical sensor arrays based on Blind Source Separation (BSS) provides a promising solution to overcome the interference problem associated with Ion-Selective Electrodes (ISE). The main motivation behind this new approach is to ease the time-demanding calibration stage. While the first works on this problem only considered the case in which the ions under analysis have equal valences, the present work aims at developing a BSS technique that works when the ions have different charges. In this situation, the resulting mixing model belongs to a particular class of nonlinear systems that have never been studied in the BSS literature. In order to tackle this sort of mixing process, we adopted a recurrent network as separating system. Moreover, concerning the BSS learning strategy, we develop a mutual information minimization approach based on the notion of the differential of the mutual information. The method works requires a batch operation, and, thus, can be used to perform off-line analysis. The validity of our approach is supported by experiments where the mixing model parameters were extracted from actual data. http://dx.doi.org/10.2516/ogst/2013194 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Duarte L.T. Jutten C. |
spellingShingle |
Duarte L.T. Jutten C. Design of Smart Ion-Selective Electrode Arrays Based on Source Separation through Nonlinear Independent Component Analysis Oil & Gas Science and Technology |
author_facet |
Duarte L.T. Jutten C. |
author_sort |
Duarte L.T. |
title |
Design of Smart Ion-Selective Electrode Arrays Based on Source
Separation through Nonlinear Independent Component Analysis |
title_short |
Design of Smart Ion-Selective Electrode Arrays Based on Source
Separation through Nonlinear Independent Component Analysis |
title_full |
Design of Smart Ion-Selective Electrode Arrays Based on Source
Separation through Nonlinear Independent Component Analysis |
title_fullStr |
Design of Smart Ion-Selective Electrode Arrays Based on Source
Separation through Nonlinear Independent Component Analysis |
title_full_unstemmed |
Design of Smart Ion-Selective Electrode Arrays Based on Source
Separation through Nonlinear Independent Component Analysis |
title_sort |
design of smart ion-selective electrode arrays based on source
separation through nonlinear independent component analysis |
publisher |
EDP Sciences |
series |
Oil & Gas Science and Technology |
issn |
1294-4475 1953-8189 |
publishDate |
2014-03-01 |
description |
The development of chemical sensor arrays based on Blind Source Separation (BSS) provides
a promising solution to overcome the interference problem associated with Ion-Selective
Electrodes (ISE). The main motivation behind this new approach is to ease the
time-demanding calibration stage. While the first works on this problem only considered
the case in which the ions under analysis have equal valences, the present work aims at
developing a BSS technique that works when the ions have different charges. In this
situation, the resulting mixing model belongs to a particular class of nonlinear systems
that have never been studied in the BSS literature. In order to tackle this sort of mixing
process, we adopted a recurrent network as separating system. Moreover, concerning the BSS
learning strategy, we develop a mutual information minimization approach based on the
notion of the differential of the mutual information. The method works requires a batch
operation, and, thus, can be used to perform off-line analysis. The validity of our
approach is supported by experiments where the mixing model parameters were extracted from
actual data.
|
url |
http://dx.doi.org/10.2516/ogst/2013194 |
work_keys_str_mv |
AT duartelt designofsmartionselectiveelectrodearraysbasedonsourceseparationthroughnonlinearindependentcomponentanalysis AT juttenc designofsmartionselectiveelectrodearraysbasedonsourceseparationthroughnonlinearindependentcomponentanalysis |
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