Improving the numerical efficiency of the B and D estimates produced by the combined deterministic-stochastic subspace identification algorithms

In this paper we find some linear dependencies on the matrices used for B and D estimation by the Van Overschee and De Moore non-biased versions of the Combined Deterministic-Stochastic Subspace Identification algorithms (CDSSI). These dependencies allow us to formulate algorithms that significantly improve the numerical efficiency on estimating these parameters without loss of accuracy. Experiences performed on practical data sets showed that the robust versions of these algorithms are twice as fast as the robust version proposed by Van Overschee and De Moore.