کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1898711 1044761 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
State and parameter estimation in stochastic dynamical models
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
State and parameter estimation in stochastic dynamical models
چکیده انگلیسی

This paper derives generalized maximum likelihood estimates of state and model parameters of a stochastic dynamical model. In contrast to previous studies, the change in background distribution due to changes in model parameters is taken into account. An ensemble approach to solving the maximum likelihood estimates is proposed. An exact solution for the ensemble update based on a square root Kalman Filter is derived. This solution involves a two step procedure in which an ensemble is first produced by a standard ensemble Kalman Filter, and then “corrected” to account for parameter estimation, thereby allowing a user to take advantage of an existing ensemble filter. The solution is illustrated with simple, low-dimensional stochastic dynamical models and shown to work well and outperform augmentation methods for estimating stochastic parameters.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica D: Nonlinear Phenomena - Volume 239, Issue 18, 15 September 2010, Pages 1781–1788
نویسندگان
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