Bayesian system identification via Markov chain Monte Carlo techniques

Brett Ninness; Soren Henriksen

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Bayesian system identification via Markov chain Monte Carlo techniques

机译：马尔可夫链蒙特卡罗技术识别贝叶斯系统

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The work here explores new numerical methods for supporting a Bayesian approach to parameter estimation of dynamic systems. This is primarily motivated by the goal of providing accurate quantification of estimation error that is valid for arbitrary, and hence even very short length data records. The main innovation is the employment of the Metropolis-Hastings algorithm to construct an ergodic Markov chain with invariant density equal to the required posterior density. Monte Carlo analysis of samples from this chain then provides a means for efficiently and accurately computing posteriors for model parameters and arbitrary functions of them.

机译：这里的工作探索了支持贝叶斯方法进行动态系统参数估计的新数值方法。这主要是出于提供对任意值有效的估计误差的准确量化的目的，因此对于非常短长度的数据记录也是如此。主要的创新是采用Metropolis-Hastings算法来构造遍历马尔可夫链，其不变密度等于所需的后验密度。然后，对来自该链的样本进行的蒙特卡洛分析提供了一种有效而准确地计算模型参数及其任意函数的后验方法。

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《Automatica》 |2010年第1期|共12页
作者
Brett Ninness; Soren Henriksen;
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原文格式 PDF
正文语种 eng
中图分类 TP1TP2;
关键词
Parameter estimation; System identification; Bayesian methods; Maximum likelihood;

机译：参数估计;系统辨识;贝叶斯方法;最大似然;

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专利

1. Bayesian system identification via Markov chain Monte Carlo techniques [J] . Brett Ninness, Soren Henriksen Automatica . 2010,第1期

机译：马尔可夫链蒙特卡罗技术识别贝叶斯系统
2. Identification of rail-sleeper-ballast system through time-domain Markov chain Monte Carlo-based Bayesian approach [J] . Lam Heung-Fai, Alabi Stephen Adeyemi, Yang Jia-Hua Engineering Structures . 2017,第JUNa1期

机译：基于时域马尔可夫链基于蒙特卡洛的贝叶斯方法识别轨枕系统
3. Bayesian Modeling of External Corrosion in Underground Pipelines Based on the Integration of Markov Chain Monte Carlo Techniques and Clustered Inspection Data [J] . Wang Hui, Yajima Ayako, Liang Robert Y., Computer-Aided Civil and Infrastructure Engineering . 2015,第4期

机译：基于马尔可夫链蒙特卡罗技术和聚类检验数据集成的地下管道外部腐蚀贝叶斯建模。
4. Bayesian System Identification of Dynamical Systems Using Reversible Jump Markov Chain Monte Carlo [C] . D. Tiboaca, P. L. Green, R. J. Barthorpe, IMAC Conference on Structural Dynamics . 2014

机译：贝叶斯系统识别可逆跳转马克洛夫链蒙特卡洛的动态系统
5. Bayesian modeling of highly structured systems using Markov chain Monte Carlo [D] . Byers, Simon David. 1998

机译：使用马尔可夫链蒙特卡洛对高度结构化系统进行贝叶斯建模
6. Bayesian and Markov chain Monte Carlo methods for identifying nonlinear systems in the presence of uncertainty [O] . P. L. Green, K. Worden -1

机译：贝叶斯和马尔可夫链蒙特卡罗方法用于在不确定性条件下识别非线性系统
7. Bayesian system identification via Markov chain Monte Carlo techniques [O] . Ninness Brett, Henriksen Soren 2010

机译：马尔可夫链蒙特卡罗技术识别贝叶斯系统
8. Bayesian Identification of a Cracked Plate using a Population-Based Markov Chain Monte Carlo Method [R] . Nichols, J. M., Moore, E. Z., Murphy, K. D. 2011

机译：基于种群的马尔可夫链蒙特卡罗方法识别裂纹板的贝叶斯识别

Bayesian system identification via Markov chain Monte Carlo techniques

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