Ensemble Kalman filter for state estimation of brain activity by considering a large scale nonlinear dynamical model
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-10-4086-3_112
Reference7 articles.
1. Dumedah Gift, Coulibaly Paulin. Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation Advances in Water Resources. 2013;60:47 - 63.
2. Tamura Hitoshi, Bacopoulos Peter, Wang Dingbao, Hagen Scott C., Kubatko Ethan J.. State estimation of tidal hydrodynamics using ensemble Kalman filter Advances in Water Resources. 2014;63:45 - 56.
3. Zuluaga Carlos D., Álvarez Mauricio A., Giraldo Eduardo. Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison Applied Energy. 2015;156:321 - 330.
4. Gillijns S., Mendoza O. B., Chandrasekar J., Moor B. L. R. De, Bernstein D. S., Ridley A.. What is the ensemble Kalman filter and how well does it work? in 2006 American Control Conference:6 pp.- 2006.
5. Hut Rolf, Amisigo Barnabas A., Steele-Dunne Susan, Giesen Nick. Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF): A data assimilation scheme for memory intensive, high performance computing Advances in Water Resources. 2015;86, Part B:273 - 283. Data assimilation for improved predictions of integrated terrestrial systems.
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