Result 1 to 20 of 94 total
Efficient computation of observation impact in 4D-Var data assimilation. (English)
Dienstfrey, Andrew M. (ed.) et al., Uncertainty quantification in scientific computing. 10th IFIP WG 2.5 working conference, WoCoUQ 2011, Boulder, CO, USA, August 1‒4, 2011. Revised selected papers. Berlin: Springer (ISBN 978-3-642-32676-9/hbk; 978-3-642-32677-6/ebook). IFIP Advances in Information and Communication Technology 377, 250-264 (2012).
1
Improving convergence in numerical analysis using observers - the wave-like equation case. (English)
Math. Models Methods Appl. Sci. 22, No. 12, 1250040,35p. (2012).
2
Performance study on CUDA gpus for parallelizing the local ensemble transformed Kalman filter algorithm. (English)
Concurrency Comput. Pract. Exp. 24, No. 2, 167-177 (2012).
3
On sequential data assimilation for scalar macroscopic traffic flow models. (English)
Physica D 241, No. 17, 1421-1440 (2012).
4
On computation of the design function gradient for the sensor-location problem in variational data assimilation. (English)
SIAM J. Sci. Comput. 34, No. 2, B127-B147 (2012).
5
On a nonlinear Kalman filter with simplified divided difference approximation. (English)
Physica D 241, No. 6, 671-680 (2012).
6
A random map implementation of implicit filters. (English)
J. Comput. Phys. 231, No. 4, 2049-2066 (2012).
7
Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters. (English)
J. Comput. Phys. 231, No. 4, 1462-1498 (2012).
8
Ensemble methods for dynamic data assimilation of chemical observations in atmospheric models. (English)
J. Algorithms Comput. Technol. 5, No. 4, 667-692 (2011).
9
Identification of strength and location of stationary point source of atmospheric pollutant in urban conditions using computational fluid dynamics model. (English)
Math. Comput. Simul. 82, No. 2, 244-257 (2011).
10
Interpolating irregularly spaced observations for filtering turbulent complex systems. (English)
SIAM J. Sci. Comput. 33, No. 5, 2620-2640 (2011).
11
Range-space variants and inexact matrix-vector products in Krylov solvers for linear systems arising from inverse problems. (English)
SIAM J. Matrix Anal. Appl. 32, No. 3, 969-986 (2011).
12
Data assimilation using a GPU accelerated path integral Monte Carlo approach. (English)
J. Comput. Phys. 230, No. 22, 8168-8178 (2011).
13
Solution of assimilation observation data problem for shallow water equations for SMP-nodes cluster. (English)
Malyshkin, Victor (ed.), Parallel computing technologies. 11th international conference, PaCT 2011, Kazan, Russia, September 19-23, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-23177-3/pbk). Lecture Notes in Computer Science 6873, 444-451 (2011).
14
The Newton method in problems of variational data assimilation: application to an infiltration model. (English)
Int. J. Pure Appl. Math. 69, No. 1, 15-32 (2011).
15
Multimodal ensemble Kalman filtering using Gaussian mixture models. (English)
Comput. Geosci. 15, No. 2, 307-323 (2011).
16
Adjoint to the Hessian derivative and error covariances in variational data assimilation. (English)
Russ. J. Numer. Anal. Math. Model. 26, No. 2, 179-188 (2011).
17
Numerical strategies for filtering partially observed stiff stochastic differential equations. (English)
J. Comput. Phys. 230, No. 3, 744-762 (2011).
18
Approximation of Bayesian inverse problems for PDEs. (English)
SIAM J. Numer. Anal. 48, No. 1, 322-345 (2010).
19
A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems. (English)
J. Signal Process. Syst. Signal Image Video Technol. 61, No. 1, 51-59 (2010).
20
Result 1 to 20 of 94 total
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