How to Avoid the Curse of Dimensionality: Scalability of Particle Filters with and without Importance Weights
نویسندگان
چکیده
منابع مشابه
How to avoid the curse of dimensionality: scalability of particle filters with and without importance weights
Particle filters are a popular and flexible class of numerical algorithms to solve a large class of nonlinear filtering problems. However, standard particle filters with importance weights have been shown to require a sample size that increases exponentially with the dimension D of the state space in order to achieve a certain performance, which precludes their use in very high-dimensional filt...
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ژورنال
عنوان ژورنال: SIAM Review
سال: 2019
ISSN: 0036-1445,1095-7200
DOI: 10.1137/17m1125340