Results 161 to 170 of about 2,193 (205)

Stochastic subspace identification via "LQ decomposition"

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
A new stochastic subspace identification algorithm is developed with the help of a stochastic realization on a finite interval. First, a finite-interval realization algorithm is re-derived via "block-LDL decomposition" for a finite string of complete covariance sequence.
Hideyuki Tanaka, Tohru Katayama
openaire   +1 more source

Stochastic realization with exogenous inputs and ‘subspace-methods’ identification

Signal Processing, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
PICCI, GIORGIO, KATAYAMA T.
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Polynomial extension of linear subspace algorithms for stochastic identification

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
Among the algorithms of linear models identification from input/output data, the N4SID (numerical sub-space state space system identification) plays an important role due to its simplicity and effectiveness. It is known that N4SDD gives good results for system identification in a Gaussian setting.
Di Loreto C, GERMANI, Alfredo, MANES, COSTANZO   +2 more
openaire   +4 more sources

Subspace Identification of Pure Stochastic Systems

2006 IEEE International Conference on Automation, Quality and Testing, Robotics, 2006
In this paper we treat the subspace identification of pure stochastic systems with no external input. The stochastic identification problem consists of computing the stochastic system matrices from given output data only. We show how this can be done using geometric operations as orthogonal projections.
D. Sendrescu, D. Popescu, E. Bobasu, E. Petre   +3 more
openaire   +1 more source

Subspace identification for a stochastic model of plague

International Journal of Biomathematics, 2016
In this paper, a stochastic model of plague is first studied by subspace identification. First, the discrete model of plague is obtained based on the classical model. The corresponding stochastic model is proposed for the existence of stochastic disturbances. Second, for the model, the parameter matrices and noise intensity are obtained.
Yu, Miao, Liu, Jianchang
openaire   +2 more sources

An experimental validation of the Stochastic Subspace Identification

PAMM, 2004
AbstractIn this contribution we derive and experimentally validate the Stochastic Subspace Identification. Additionally we compare the results with an updated finite element model. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
A. S. Kompalka, S. Reese
openaire   +1 more source

Stochastic subspace identification of linear systems with observation outliers

Proceedings of the 44th IEEE Conference on Decision and Control, 2006
This paper considers a problem of identifying stochastic linear systems subject to observation outliers, where the observation noise contains large values with a low probability. A stochastic subspace identification method for the problem is developed based on a block LQ decomposition, introducing a weighting matrix to delete outputs which are ...
Hideyuki Tanaka, Jaafar AlMutawa, Tohru Katayama   +2 more
openaire   +1 more source

N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems

Automatica, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peter Van Overschee, Bart De Moor
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On “Subspace Methods” Identification and Stochastic Model Reduction

IFAC Proceedings Volumes, 1994
Abstract In this paper the problem of stochastic model identification from estimated covariances is considered. In this context, we analyze a class of popular subspace identification procedures in the theoretical framework of rational covariance extension and balanced model reduction, and we demonstrate that they are based on a hidden assumption ...
Anders Lindquist, Giorgio Picci
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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
openaire   +1 more source