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Communication Dans Un Congrès Année : 2017

Non-negative decomposition of geophysical dynamics

Résumé

The decomposition of geophysical processes into relevant modes is a key issue for characterization, forecasting and reconstruction problems. The blind separation of contributions from different sources is a well-studied problem in signal and image processing. Recently, significant advances have been reported with the introduction of non-negative and sparse formulations. In this work, we address an extension to the blind decomposition of linear operators or transfer functions between variables of interest with an emphasis on a non-negative setting. As illustrated here, such decompositions are of key interest for the analysis of geophysical dynamics and the relationships between different geophysical variables.
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Dates et versions

hal-01596464 , version 1 (27-09-2017)

Identifiants

  • HAL Id : hal-01596464 , version 1

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Manuel Lopez Radcenco, Abdeldjalil Aissa El Bey, Pierre Ailliot, Ronan Fablet. Non-negative decomposition of geophysical dynamics. ESANN 2017 : 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2017, Bruges, Belgium. ⟨hal-01596464⟩
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