34 research outputs found
L\u27herborisation A La Moucherolle Et Dans Ses Alentours
Volume: 7Start Page: 740End Page: 75
Caractérisation optique de réseaux de diffraction submicroniques par des techniques génétique et neuronale
Les efforts consentis dans les annĂ©es rĂ©centes dans la conception de rĂ©seaux de diffraction de pĂ©riode rĂ©duite ont conduit Ă atteindre les limites de rĂ©solution des diffĂ©rents techniques de caractĂ©risation microscopiques utilisĂ©es jusqu'alors. De nouvelles mĂ©thodes doivent ĂȘtre mises au point afin de permettre une bonne adĂ©quation entre les formes espĂ©rĂ©es et celles effectivement rĂ©alisĂ©es. Une solution efficace consiste Ă rĂ©soudre le problĂšme inverse de la diffraction. Ainsi, il est possible de remonter au profil du rĂ©seau connaissant un certain nombre d'efficacitĂ©s diffractĂ©es appelĂ© signature optique sous un certaines hypothĂšses. Nous avons montrĂ© expĂ©rimentalement l'efficacitĂ© de deux mĂ©thodes basĂ©es d'une part sur l'utilisation des algorithmes gĂ©nĂ©tiques et d'autre part sur les rĂ©seaux neuronaux. La premiĂšre se rĂ©vĂšle ĂȘtre d'une trĂšs grande robustesse et flexibilitĂ©. Le traitement de la seconde est extrĂȘmement rapide et peut ainsi permettre un contrĂŽle de l'homogĂ©nĂ©itĂ© d'un rĂ©seauRecent development in the field of grating fabrication with submicrometer period leads to reach the resolution limit of classical microscopic caracterization techniques. New methods need to be finalised to produce a good checking of the realised structures. The resolution of the inverse scattering problem can be a good alternative. Thus, it is possible to reconstruct the grating profile from a set of diffracted efficiencies orders called optical signature under some hypothesis. The efficiency of two methods based respectively on the use of a genetic algorithm and a neural network is experimentally demonstrated. The first one is a robust and flexible technique. On the other hand, the speed of the second one permits to accomplish a control of the grating homogeneityST ETIENNE-BU Sciences (422182103) / SudocSudocFranceF
CaractĂ©risation de rĂ©seaux optiques par lâutilisation de rĂ©seaux neuronaux
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RĂ©solution dâun problĂšme inverse par une approche neuronale. Application Ă la caractĂ©risation de rĂ©seaux optiques
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Réduction du temps de contrÎle de réseaux de diffraction submicroniques
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Resolution of inverse problem by use of a Neural Network: Application to the characterization of optical grating
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Control of the homogeneity of an optical grating by a neural characterization
International audienceProgress in microelectronics has allowed the fabrication of optical gratings with small period-to-wavelength ratios, which are very useful in several applications, such as telecommunication and optical sensors. A rapid and nondestructive characterization process is essential to check the agreement of the produced with the expected structure. The main difficulty is in assuring sufficient homogeneity all along the grating surface. We show that neural characterization coupled with neural selection can be efficiently applied to this quality measurement. Depicted results concern a 1-”m-period grating fabricated by reactive ion etching on a silicon substrate
CaractĂ©risation de composants optiques par des techniques dâintelligence artificielle
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