dc.creatorShkvarko, Yuriy
dc.creatorVillalón-Turrubiates, Iván E.
dc.date2016-04-04T21:04:34Z
dc.date2016-04-04T21:04:34Z
dc.date2005
dc.date.accessioned2023-07-21T21:57:24Z
dc.date.available2023-07-21T21:57:24Z
dc.identifierY. Shkvarko & I.E. Villalón-Turrubiate (2005), “Real-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing”. Proceedings of the 17th International Association for Mathematics and Computers in Simulation (IMACS) World Congress, París, Francia.
dc.identifierhttp://hdl.handle.net/11117/3234
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7756036
dc.descriptionThe robustified numerical technique for real-time sensor array reconstructive image processing is developed as required for remote sensing imaging with large scale array/synthesized array radars. The addressed technique is designed via performing the regularized robustification of the fused Bayesian-regularization imaging method aggregated with the efficient real-time numerical implementation scheme that employs the neural network computing.
dc.descriptionCINVESTAV
dc.formatapplication/pdf
dc.languageeng
dc.publisherAssociation for Mathematics and Computers in Simulation
dc.relationIMACS;17h
dc.rightshttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdf
dc.subjectImage Reconstruction
dc.subjectRegularization
dc.subjectNeural Networks
dc.titleReal-Time Reconstruction of Remote Sensing Imagery: Aggregation of Robust Regularization with Neural Computing
dc.typeinfo:eu-repo/semantics/conferencePaper


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