An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment

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dc.contributor.authorde Cos Juez, Francisco J.
dc.contributor.authorSanchez Lasheras, Fernando
dc.contributor.authorRoqueni, Nieves
dc.contributor.authorOsborn, James
dc.date.accessioned2024-01-10T13:45:45Z
dc.date.available2024-01-10T13:45:45Z
dc.date.issued2012
dc.description.abstractIn astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A).
dc.description.funderSpanish Science and Innovation Ministry
dc.description.funderSchool of Engineering, Pontificia Universidad Catolica de Chile
dc.description.funderEuropean Southern Observatory
dc.fechaingreso.objetodigital2024-05-23
dc.format.extent17 páginas
dc.fuente.origenWOS
dc.identifier.doi10.3390/s120708895
dc.identifier.issn1424-8220
dc.identifier.pubmedidMEDLINE:23012524
dc.identifier.urihttps://doi.org/10.3390/s120708895
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/79074
dc.identifier.wosidWOS:000306796500027
dc.information.autorucIngeniería;Osborn J;S/I;1009804
dc.issue.numero7
dc.language.isoen
dc.nota.accesoContenido completo
dc.pagina.final8911
dc.pagina.inicio8895
dc.publisherMDPI
dc.revistaSENSORS
dc.rightsacceso abierto
dc.subjectMOAO
dc.subjectadaptive
dc.subjectoptics
dc.subjectneural
dc.subjectnetworks
dc.subjectreconstructor
dc.subjectZernike
dc.subjectOPTIMAL LINEAR-COMBINATIONS
dc.subjectARTIFICIAL NEURAL-NETWORKS
dc.subjectADAPTIVE-OPTICS
dc.subjectPERFORMANCE
dc.subjectHARDWARE
dc.subjectNONLINEARITIES
dc.subjectPRINCIPLES
dc.subject.ods13 Climate Action
dc.subject.odspa13 Acción por el clima
dc.titleAn ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment
dc.typeartículo
dc.volumen12
sipa.codpersvinculados1009804
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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