Guaranteed stability with subspace methods
Systems & Control Letters
Realization of stable models with subspace methods
Automatica (Journal of IFAC)
A subspace algorithm for the identification of discrete time frequency domain power spectra
Automatica (Journal of IFAC)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Experimental evidence showing that stochastic subspace identification methods may fail
Systems & Control Letters
Modifications of rational transfer matrices to achieve positive realness
Signal Processing
Brief paper: An insight into instrumental variable frequency-domain subspace identification
Automatica (Journal of IFAC)
Subspace-based rational interpolation of analytic functions from phase data
IEEE Transactions on Signal Processing
Vector ARMA estimation: a reliable subspace approach
IEEE Transactions on Signal Processing
On the parameterization of positive real sequences and MA parameterestimation
IEEE Transactions on Signal Processing
Frequency-domain subspace system identification using non-parametric noise models
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Robust spectral factor approximation of discrete-time frequency domain power spectras
Automatica (Journal of IFAC)
Decoding by linear programming
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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In this paper, we propose a subspace algorithm for the identification of linear-time-invariant discrete-time systems with more outputs than inputs from measured power spectrum data. The proposed identification algorithm is interpolatory and strongly consistent when the corruptions in the spectrum measurements have a bounded covariance function. Asymptotic performance and the interpolation properties of the proposed algorithm are illustrated by means of a numerical example.