Dimensional reduction for a Bayesian filter

Chorin AJ; Krause P

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Dimensional reduction for a Bayesian filter

机译：贝叶斯滤波器的降维

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摘要

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.

机译：提出了一种自适应策略，用于在针对非线性动力学的贝叶斯滤波器的顺序蒙特卡罗实现中，在提案分配的计算中减少未知数。这个想法是只解决动态扩展的方向，自适应地找到。此策略由最佳预测的早期工作提出。该构造应在数据同化（例如地球物理流体动力学）中具有价值。

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《Proceedings of the National Academy of Sciences of the United States of America》 |2004年第42期|p.15013-15017|共5页
作者
Chorin AJ; Krause P;
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作者单位

Department of Mathematics, University of California, Berkeley, CA 94720, USA. chroin@math.berkeley.edu;

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收录信息美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
原文格式 PDF
正文语种 eng
中图分类自然科学总论;
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6. Dimensional reduction for a Bayesian filter [O] . Alexandre J. Chorin, Paul Krause 2004

机译：贝叶斯滤波器的降维
7. Dimensional reduction for a Bayesian filter [O] . Chorin, Alexandre J., Krause, Paul 2004

机译：贝叶斯滤波器的降维

Dimensional reduction for a Bayesian filter

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