Results 211 to 220 of about 33,160 (233)

Recursive Subspace Identification Algorithm for Closed-loop Stochastic Systems

IFAC Proceedings Volumes, 2009
Abstract A recursive subspace identification algorithm is proposed for the closed-loop stochastic systems in state-space form. Each recursion step consists of two-stages: first, the innovation of the stochastic system is estimated by the extended least squares (ELS) algorithm; then, a basis of the extended observability matrix is estimated by the ...
YuePing Jiang, HaiTao Fang
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Subspace identification for a stochastic model of bubonic plague

2016 35th Chinese Control Conference (CCC), 2016
Based on the model of bubonic plague, the corresponding stochastic model with stochastic disturbances is given. According to the data of bubonic plague from the World Health Organization, the coefficient matrices and noise intensity of the model are obtained by subspace identification method.
Miao Yu, Jianchang Liu, Lichun Zhao, Honghai Wang, Yu Zhang   +4 more
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Operational Modal Analysis Using a Fast Stochastic Subspace Identification Method

Stochastic subspace identification methods are an efficient tool for system identification of mechanical systems in Operational Modal Analysis, where modal parameters (natural frequencies, damping ratios, mode shapes) are estimated from measured ambient vibration data of a structure.
Döhler, Michael, Andersen, Palle, Mevel, Laurent   +2 more
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Stochastic subspace identification of linear systems with observation outliers

21st Mediterranean Conference on Control and Automation, 2013
We propose a diagnostic for the state space model fitting time series formed by deleting observations from the data and measuring the change in the estimates of the parameters. A method is proposed for distinguishing an observational outlier from an innovational one.
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A Note on LQ Decomposition in Stochastic Subspace Identification

2010
In this paper, we consider the role of LQ decomposition in the realization-based subspace identification method for discrete-time stochastic systems as a continuation of our earlier work [6] in deterministic setting. Under the assumption that the past horizon of the data matrix is infinite, we reveal a nice block lower triangular structure of a certain
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Uncertainty bounds on modal parameters obtained stochastic subspace identification

2008
The modal parameters of a structure that are estimated from ambient vibration measurements are always subject to bias and variance errors. In this paper, it is discussed how part of the bias errors can be removed and how the variance errors can be estimated from a single ambient vibration test.
Reynders, E., Pintelon, Rik, De Roeck, Guido   +2 more
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Modal Identification of Civil Structures via Stochastic Subspace Algorithm with Monte Carlo–Based Stabilization Diagram

Journal of Structural Engineering, 2022
Kang Zhou, Qiu Sheng Li, Xuliang Han
exaly  

Machine learning-based stochastic subspace identification method for structural modal parameters

Engineering Structures, 2023
Yuequan Bao
exaly  

Enhancing the performance of stochastic subspace identification method via energy-oriented categorization of modal components

Engineering Structures, 2021
Ji-Yang Fu
exaly  

A NOVEL VARIATIONAL BAYESIAN APPROACH TO STOCHASTIC SUBSPACE IDENTIFICATION

Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019), 2023
Brandon J. O'Connell, Max D. Champneys, Elizabeth J. Cross, Timothy J. Rogers   +3 more
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