Estimation of General Nonlinear State-Space Systems, Report no. LiTH-ISY-R-3001
نویسندگان
چکیده
This paper presents a novel approach to the estimation of a general class of dynamic nonlinear system models. The main contribution is the use of a tool from mathematical statistics, known as Fishers' identity, to establish how so-called particle smoothing methods may be employed to compute gradients of maximum-likelihood and associated prediction error cost criteria.
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تاریخ انتشار 2011