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[Other resourceReBEL_0-2-6

Description: ReBEL is a Matlabtoolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and Kalman filtering by Rudolph van der Merwe and Eric A. Wan. The code is developed and maintained by Rudolph van der Merwe at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University). -ReBEL is a Matlabtoolkit of functions and s cripts. designed to facilitate in sequential Bayesian ference (estimation) in general state space mo dels. This software consolidates research on n ew methods for Bayesian estimation a recursive nd Kalman filtering by Rudolph and van der Merwe Eric A. Wan. The code is developed and maintaine d by Rudolph van der Merwe at the OGI School of Sci ence
Platform: | Size: 489335 | Author: 薛斌 | Hits:

[Network DevelopRECURSIVE BAYESIAN INFERENCE ON

Description:

This thesis is concerned with recursive Bayesian estimation of non-linear dynamical
systems, which can be modeled as discretely observed stochastic differential
equations. The recursive real-time estimation algorithms for these continuous-
discrete filtering problems are traditionally called optimal filters and the algorithms
for recursively computing the estimates based on batches of observations
are called optimal smoothers. In this thesis, new practical algorithms for approximate
and asymptotically optimal continuous-discrete filtering and smoothing are
presented.
The mathematical approach of this thesis is probabilistic and the estimation
algorithms are formulated in terms of Bayesian inference. This means that the
unknown parameters, the unknown functions and the physical noise processes are
treated as random processes in the same joint probability space. The Bayesian approach
provides a consistent way of computing the optimal filtering and smoothing
estimates, which are optimal given the model assumptions and a consistent
way of analyzing their uncertainties.
The formal equations of the optimal Bayesian continuous-discrete filtering
and smoothing solutions are well known, but the exact analytical solutions are
available only for linear Gaussian models and for a few other restricted special
cases. The main contributions of this thesis are to show how the recently developed
discrete-time unscented Kalman filter, particle filter, and the corresponding
smoothers can be applied in the continuous-discrete setting. The equations for the
continuous-time unscented Kalman-Bucy filter are also derived.
The estimation performance of the new filters and smoothers is tested using
simulated data. Continuous-discrete filtering based solutions are also presented to
the problems of tracking an unknown number of targets, estimating the spread of
an infectious disease and to prediction of an unknown time series.


Platform: | Size: 1457664 | Author: eestarliu | Hits:

[AI-NN-PRReBEL_0-2-6

Description: ReBEL is a Matlabtoolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and Kalman filtering by Rudolph van der Merwe and Eric A. Wan. The code is developed and maintained by Rudolph van der Merwe at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University). -ReBEL is a Matlabtoolkit of functions and s cripts. designed to facilitate in sequential Bayesian ference (estimation) in general state space mo dels. This software consolidates research on n ew methods for Bayesian estimation a recursive nd Kalman filtering by Rudolph and van der Merwe Eric A. Wan. The code is developed and maintaine d by Rudolph van der Merwe at the OGI School of Sci ence
Platform: | Size: 489472 | Author: 薛斌 | Hits:

[AlgorithmReBEL_0-2-6

Description: 递归贝叶斯估计的工具包,旨在方便序列贝叶斯估计-A Matlab toolkit for Recursive Bayesian Estimation
Platform: | Size: 489472 | Author: 刘民 | Hits:

[matlabReBEL-0.2.7

Description: ReBEL is a Matlab® toolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and Kalman filtering by Rudolph van der Merwe and Eric A. Wan at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University-ReBEL is a Matlab® toolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and Kalman filtering by Rudolph van der Merwe and Eric A. Wan at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University
Platform: | Size: 1703936 | Author: hoanglaota | Hits:

[matlabxitongbianshi

Description: 贝叶斯估计,最小二乘法,递推最小二乘法,梯度校正法,增广最小二乘法进行系统辨识-Bayesian estimation, least squares, recursive least squares method, the gradient correction method, the augmented least squares method for system identification
Platform: | Size: 24576 | Author: James | Hits:

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