An adaptive strategy is proposed for reducing the number of unknowns in the calculation of a proposal distribution in a sequential Monte Carlo implementation of a Bayesian filter for nonlinear dynamics. The idea is to solve only in directions in which the dynamics is expanding, found adaptively; this strategy is suggested by earlier work on optimal prediction. The construction should be of value in data assimilation, for example, in geophysical fluid dynamics.
CITATION STYLE
Chorin, A. J., & Krause, P. (2004). Dimensional reduction for a Bayesian filter. Proceedings of the National Academy of Sciences of the United States of America, 101(42), 15013–15017. https://doi.org/10.1073/pnas.0406222101
Mendeley helps you to discover research relevant for your work.