Noise estimation for hyperspectral subspace identification on FPGAs
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Altres documents de l'autoria: León, Germán; González, Carlos; Mayo, Rafael; Mozos, Daniel; Quintana-Orti, Enrique S.
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Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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Noise estimation for hyperspectral subspace identification on FPGAsData de publicació
2019-05Editor
SpringerCita bibliogràfica
León, G., González, C., Mayo, R. et al. J Supercomput (2019) 75: 1323.Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://link.springer.com/article/10.1007/s11227-018-2425-3Versió
info:eu-repo/semantics/submittedVersionParaules clau / Matèries
Resum
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)Drets d'accés
© Springer Science+Business Media, LLC, part of Springer Nature 2018
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info:eu-repo/semantics/openAccess
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info:eu-repo/semantics/openAccess
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