The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
En 2001, le microsatellite DEMETER sera lancé pour effectuer la détection des émissions électromagnétiques transmises par les régions sismiques. Son objectif scientifique principal est lié à l'étude des perturbations ionosphériques dues à l'activité sismique et volcanique. Un système permettant une identification et une caractérisation embarquées de structures spatialement et temporellement cohérentes associé à la mesure d'une ou plusieurs composantes du champ d'ondes électromagnétiques est utilisé. Il est basé sur des réseaux de neurones. Le choix et l'entraînement du réseau de neurones se font sur le terrain à partir des formes d'onde disponibles. Les paramètres du système de réseau neuronal sont ensuite transmis au satellite. Ce processus de reconfiguration peut être répété chaque fois que nécessaire au cours de la mission spatiale. Des détails sur le fonctionnement et l'optimisation du codage pour la mise en œuvre de DSP sont présentés. La première fonction de ce système qui sera assurée sur le satellite DEMETER est l'identification et la caractérisation en temps réel des phénomènes de sifflement. Une application à l'analyse de tels phénomènes observés dans les données du satellite AUREOL-3 est exposée.
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Franck ELIE, Masashi HAYAKAWA, Michel PARROT, Jean-Louis PINÇON, Francois LEFEUVRE, "Neural Network System for the Analysis of Transient Phenomena on Board the DEMETER Micro-Satellite" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 8, pp. 1575-1581, August 1999, doi: .
Abstract: In 2001, the DEMETER micro-satellite will be launched to perform Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions. Its main scientific objective is related to the investigation of the ionospheric perturbations due to the seismic and volcanic activity. A system allowing an onboard identification and characterization of spatially and temporally coherent structures associated with the measurement of one or several electromagnetic wave field components is used. It is based on neural networks. The choice and training of the neural network are done on the ground from available waveforms. The parameters of the neural network system are then transmitted to the satellite. This reconfiguration process can be repeated whenever necessary during the space mission. Details about the functioning and coding optimization for DSP implementation is presented. The first function of this system which will be performed on the satellite DEMETER is the real-time identification and characterization of whistler phenomena. An application to the analysis of such phenomena observed in data from the AUREOL-3 satellite is exposed.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_8_1575/_p
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@ARTICLE{e82-a_8_1575,
author={Franck ELIE, Masashi HAYAKAWA, Michel PARROT, Jean-Louis PINÇON, Francois LEFEUVRE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Neural Network System for the Analysis of Transient Phenomena on Board the DEMETER Micro-Satellite},
year={1999},
volume={E82-A},
number={8},
pages={1575-1581},
abstract={In 2001, the DEMETER micro-satellite will be launched to perform Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions. Its main scientific objective is related to the investigation of the ionospheric perturbations due to the seismic and volcanic activity. A system allowing an onboard identification and characterization of spatially and temporally coherent structures associated with the measurement of one or several electromagnetic wave field components is used. It is based on neural networks. The choice and training of the neural network are done on the ground from available waveforms. The parameters of the neural network system are then transmitted to the satellite. This reconfiguration process can be repeated whenever necessary during the space mission. Details about the functioning and coding optimization for DSP implementation is presented. The first function of this system which will be performed on the satellite DEMETER is the real-time identification and characterization of whistler phenomena. An application to the analysis of such phenomena observed in data from the AUREOL-3 satellite is exposed.},
keywords={},
doi={},
ISSN={},
month={August},}
Copier
TY - JOUR
TI - Neural Network System for the Analysis of Transient Phenomena on Board the DEMETER Micro-Satellite
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1575
EP - 1581
AU - Franck ELIE
AU - Masashi HAYAKAWA
AU - Michel PARROT
AU - Jean-Louis PINÇON
AU - Francois LEFEUVRE
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 1999
AB - In 2001, the DEMETER micro-satellite will be launched to perform Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions. Its main scientific objective is related to the investigation of the ionospheric perturbations due to the seismic and volcanic activity. A system allowing an onboard identification and characterization of spatially and temporally coherent structures associated with the measurement of one or several electromagnetic wave field components is used. It is based on neural networks. The choice and training of the neural network are done on the ground from available waveforms. The parameters of the neural network system are then transmitted to the satellite. This reconfiguration process can be repeated whenever necessary during the space mission. Details about the functioning and coding optimization for DSP implementation is presented. The first function of this system which will be performed on the satellite DEMETER is the real-time identification and characterization of whistler phenomena. An application to the analysis of such phenomena observed in data from the AUREOL-3 satellite is exposed.
ER -