Using a stacked-autoencoder neural network model to estimate sea state bias for a radar altimeter

This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training dataset, and the other 2 cycles of the GDR from Jason-...

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Detalles Bibliográficos
Autores principales: Miao, Xiangying, Miao, Hongli, Jia, Yongjun, Guo, Yingting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296554/
https://www.ncbi.nlm.nih.gov/pubmed/30557315
http://dx.doi.org/10.1371/journal.pone.0208989

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6296554/
https://www.ncbi.nlm.nih.gov/pubmed/30557315
http://dx.doi.org/10.1371/journal.pone.0208989

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