Title: Subspace algorithms for the stochastic identification problem
Authors: Vanoverschee, P ×
De Moor, Bart #
Issue Date: May-1993
Publisher: Pergamon-elsevier science ltd
Series Title: Automatica vol:29 issue:3 pages:649-660
Abstract: In this paper, we derive a new subspace algorithm to consistently identify stochastic state space models from given output data without forming the covariance matrix and using only semi-infinite block Hankel matrices. The algorithm is based on the concept of principal angles and directions. We describe how they can be calculated with QR and Quotient Singular Value Decomposition. We also provide an interpretation of the principal directions as states of a non-steady state Kalman filter bank.
ISSN: 0005-1098
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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