Marginalized Particle Filters for Mixed Linear/Non-linear State-space Models Export

@misc{Schon, abstract = {The particle filter offers a general numerical tool to approximate the posterior density function for the state in nonlinear and non-Gaussian filtering problems. While the particle filter is fairly easy to implement and tune, its main drawback is that it is quite computer intensive. However, due to faster computers this drawback can be overcome and as a result the particle filter has quickly become a popular tool in signal processing applications. The computational complexity increases quickly...}, author = {Sch\"{o}n, Thomas and Gustafsson, Fredrik and Nordlund, Per-Johan}, citeulike-article-id = {347941}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.2903}, keywords = {ee520, ee520\_part1, filtering, particle-filtering}, posted-at = {2005-10-11 16:55:16}, priority = {2}, title = {Marginalized Particle Filters for Mixed Linear/Non-linear State-space Models}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.2903} }

TY - GEN ID - Schon L3 - citeulike-article-id:347941 N2 - The particle filter offers a general numerical tool to approximate the posterior density function for the state in nonlinear and non-Gaussian filtering problems. While the particle filter is fairly easy to implement and tune, its main drawback is that it is quite computer intensive. However, due to faster computers this drawback can be overcome and as a result the particle filter has quickly become a popular tool in signal processing applications. The computational complexity increases quickly... TI - Marginalized Particle Filters for Mixed Linear/Non-linear State-space Models KW - ee520 KW - ee520_part1 KW - filtering KW - particle-filtering AU - Schön, Thomas AU - Gustafsson, Fredrik AU - Nordlund, Per-Johan UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.4.2903 ER -