Results 191 to 200 of about 33,160 (233)

Subspace algorithms for the stochastic identification problem

[1991] Proceedings of the 30th IEEE Conference on Decision and Control, 1993
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Van Overschee, Peter, De Moor, Bart
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An improved stochastic subspace identification for operational modal analysis

Measurement, 2012
Abstract An improved stochastic subspace identification algorithm is introduced to solve the low computational efficiency problem of the Data-driven stochastic subspace identification. Compared with the conventional algorithm, it needs much less cost of memory and computing time because it does not have a process of the QR decomposition of Hankel ...
Guowen Zhang, Baoping Tang, Guangwu Tang
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Fast online implementation of covariance-driven stochastic subspace identification

Mechanical Systems and Signal Processing, 2023
Siyuan Sun, Bin Yang, Qilin Zhang, Roland Wüchner, Licheng Pan, Haitao Zhu   +5 more
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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.
H. Tanaka, T. Katayama
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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
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Stochastic realization with exogenous inputs and ‘subspace-methods’ identification

Signal Processing, 1996
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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
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Electromechanical mode estimation using recursive adaptive stochastic subspace identification

2014 IEEE PES T&D Conference and Exposition, 2014
Measurement based algorithms for estimating low-frequency electromechanical modes serve as useful practical methods to monitor the modal properties of power system oscillations in real-time. This paper proposes a recursive adaptive stochastic subspace identification (RASSI) algorithm for online monitoring of power system modes using wide-area ...
S. A. Nezam Sarmadi, Vaithianathan Venkatasubramanian   +1 more
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Modal identification of arch dams using balanced stochastic subspace identification

Journal of Vibration and Control, 2016
Dynamic characteristics extracted from ambient and forced vibration tests are always associated with some level of uncertainties because of unknown nature of applied forces, existence of ambient noises as well as measurement errors. Stochastic Subspace Methods are among the most accurate and consistent methods within the domain of operational modal ...
Reza Tarinejad, Mehran Pourgholi
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Oscillatory Stability Limit Prediction Using Stochastic Subspace Identification

IEEE Transactions on Power Systems, 2006
Determining stability limits and maximum loading margins in a power system is important and can be of significant help for system operators for preventing stability problems. In this paper, stochastic subspace identification is employed to extract the critical mode(s) from the measured ambient noise without requiring artificial disturbances (e.g., line
H. Ghasemi, C.A. Canizares, A. Moshref
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