In signal processing and control applications, on-line state estimation plays important role in stability of the system. In cases where state and/or measurement functions are highly nonlinear and/or the noise is not Gaussian, conventional filters such as extended Kalman filters do not provide satisfactory results. In this paper, particle filters and its application to a nonlinear problem are examined.
|Translated title of the contribution||Reduction of sensory inaccuracy in nonlinear systems using particle filters|
|Title of host publication||2006 IEEE 14th Signal Processing and Communications Applications Conference|
|State||Published - Dec 1 2006|
|Event||2006 IEEE 14th Signal Processing and Communications Applications - Antalya, Turkey|
Duration: Apr 17 2006 → Apr 19 2006
|Name||2006 IEEE 14th Signal Processing and Communications Applications Conference|
|Period||4/17/06 → 4/19/06|