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27 April 2010Feynman path integral inspired computational methods for
nonlinear filtering
The fundamental solution for the continuous-time filtering problems can be expressed in terms of Feynman path
integrals. This enables one to view the solution of filtering problem in terms of an effective action that is a function
of the signal and measurement models. The practical utility of the path integral formula is demonstrated via
some nontrivial examples. Specifically, it is shown that the simplest approximation of the path integral formula
for the fundamental solution of the Fokker-Planck-Kolmogorov forward equation (termed the Dirac-Feynman
approximation) can be applied to solve nonlinear continuous-discrete filtering problems quite accurately using
sparse grid filtering and Monte-Carlo approaches.
Bhashyam Balaji
"Feynman path integral inspired computational methods for
nonlinear filtering", Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 769708 (27 April 2010); https://doi.org/10.1117/12.849698
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Bhashyam Balaji, "Feynman path integral inspired computational methods for nonlinear filtering," Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 769708 (27 April 2010); https://doi.org/10.1117/12.849698