Treffer: A post-non-linear source separation algorithm for bounded magnitude sources and its application to ISFETs

Title:
A post-non-linear source separation algorithm for bounded magnitude sources and its application to ISFETs
Authors:
BERMEJO, Sergio
Source:
Neurocomputing (Amsterdam). 148:477-486
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 42 ref
Original Material:
INIST-CNRS
Subject Terms:
Cognition, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Physique, Physics, Generalites, General, Instruments, appareillage, composants et techniques communs à plusieurs branches de la physique et de l'astronomie, Instruments, apparatus, components and techniques common to several branches of physics and astronomy, Techniques et équipements généraux, General equipment and techniques, Capteurs (chimiques, optiques, électriques, de mouvement, de gaz, etc.); télédétection, Sensors (chemical, optical, electrical, movement, gas, etc.); remote sensing, Sciences appliquees, Applied sciences, Electronique, Electronics, Electronique des semiconducteurs. Microélectronique. Optoélectronique. Dispositifs à l'état solide, Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices, Transistors, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Analyse composante indépendante, Independent component analysis, Analisis componente independiente, Aveugle, Blind, Ciego, Calcul formel, Computer algebra, Cálculo formal, Effet non linéaire, Non linear effect, Efecto no lineal, Etalonnage, Calibration, Contraste, Etude expérimentale, Experimental study, Estudio experimental, Identification aveugle, Blind identification, Identificación ciega, Information mutuelle, Mutual information, Información mutual, Mesure, Measurement, Medida, Mélange signal, Signal mixing, Mezcla señal, Méthode séparation, Separation method, Método separación, Source linéaire, Linear source, Fuente lineal, Séparation aveugle, Blind separation, Separación ciega, Séparation source, Source separation, Separación señal, Transformation échelle, Scale transformation, Transformación escala, Transistor effet champ sensible ion, Ionosensible field effect transistor, Transistor efecto campo sensible ión, Transistor effet champ, Field effect transistor, Transistor efecto campo, Capteur intelligent, Intelligent sensors, Sensor inteligente, Ion-selective field-effect transistors, Nonlinear blind source separation, Post-nonlinear mixtures, Smart sensors
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Electronic Engineering, Universitat Politècnica de Catalunya, Jordi Cirona 1-3, 08034 Barcelona, Spain
ISSN:
0925-2312
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28844561
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Electronics

Metrology

Telecommunications and information theory
Accession Number:
edscal.28844561
Database:
PASCAL Archive

Weitere Informationen

The response of ion-sensitive field-effect transistors (ISFETs) can be seriously affected in mixed-ion solutions by different interfering ions. As has been demonstrated, this problem can be addressed using nonlinear semi-blind source separation (BSS) algorithms based on post-non-linear mixtures in which nonlinear transforms must be computed using supervised samples, i.e. calibration points for known concentrations of the main ion. In order to eliminate the cost of collecting such samples, this paper introduces a novel non-linear BSS algorithm that employs linearizing transforms computed only with unsupervised information. The scale indeterminacy of this transform is removed using a prior on the sources based on magnitude bounding and, besides, gaussianization is generalized by using a kernel estimator. Experiments with real ISFET measurements demonstrate that this BSS algorithm achieves a level of accuracy similar to that of the semi-blind counterpart based on independent component analysis and outperforms a post-nonlinear BSS algorithm which minimizes the mutual information.