Noise estimation for hyperspectral subspace identification on FPGAs
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Otros documentos de la autoría: León, Germán; González, Carlos; Mayo, Rafael; Mozos, Daniel; Quintana-Orti, Enrique S.
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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Título
Noise estimation for hyperspectral subspace identification on FPGAsFecha de publicación
2019-05Editor
SpringerCita bibliográfica
León, G., González, C., Mayo, R. et al. J Supercomput (2019) 75: 1323.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s11227-018-2425-3Versión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
Resumen
We present a reliable and efficient FPGA implementation of a procedure for the computation of the noise estimation matrix, a key stage for subspace identification of hyperspectral images. Our hardware realization is ... [+]
We present a reliable and efficient FPGA implementation of a procedure for the computation of the noise estimation matrix, a key stage for subspace identification of hyperspectral images. Our hardware realization is based on numerically stable orthogonal transformations, avoids the numerical difficulties of the normal equations method for the solution of linear least squares problems (LLS), and exploits the special relations between coupled LLS problems arising in the hyperspectral image. Our modular implementation decomposes the QR factorization that comprises a significant part of the cost into a sequence of suboperations, which can be efficiently computed on an FPGA. [-]
Proyecto de investigación
MINECO (Projects TIN2014-53495-R and TIN2013-40968-P)Derechos de acceso
© Springer Science+Business Media, LLC, part of Springer Nature 2018
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info:eu-repo/semantics/openAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/openAccess
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