Subspace-based methods for system identification have attracted much attention during the
past few years. This interest is due to the ability of providing accurate state-space models for …

Numerous important results in signal processing and system theory have been obtained by
means of rst-and second-order tools: vector-and matrix algebra, from an algebraic point of …

In this paper, the authors use the Numerical algorithm for Subspace State Space System
IDentification (N4SID) to extract dynamic parameters from phasor measurements collected …

The frequency and damping of electromechanical modes offer considerable insight into the
dynamic stability properties of a power system. The performance properties of three mode …

We consider the problem of identifying multivariable finite dimensional linear time-invariant
systems from noisy input/output measurements. Apart from the fact that both the measured …

The problem of MIMO recursive identification is analyzed within the framework of subspace
model identification (SMI) and the use of recent signal processing algorithms for the …

Complex function theory and linear algebra provide much of the basic mathematics needed
by engineers engaged in numerical computations, signal processing or control. The transfer …

The so-called subspace methods for direct identification of linear models in state space form
have drawn considerable interest recently. They have been found to work well in many …

In this paper we present a new subspace identification algorithm for the identification of multi-
input multi-output linear time-invariant continuous-time systems from measured frequency …

The authors generalize linear subspace identification theory to an analog theory for the
subspace identification of bilinear systems. A major assumption they make is that the inputs …