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ICASSP
2009
IEEE

Functional estimation in Hilbert space for distributed learning in wireless sensor networks

10 years 4 months ago
Functional estimation in Hilbert space for distributed learning in wireless sensor networks
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new sparsiļ¬cation criterion for online learning. As opposed to previously derived criteria, it is based on the estimated error and is therefore is well suited for tracking the evolution of systems over time. We also derive a gradient descent algorithm, and we demonstrate its relevance to estimate the dynamic evolution of temperature in a given region.
Paul Honeine, Cédric Richard, José C
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Paul Honeine, Cédric Richard, José Carlos M. Bermudez, Hichem Snoussi, Mehdi Essoloh, François Vincent
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