Abstract
It is known that certain popular stochastic subspace identification methods may fail for theoretical reasons related to positive realness. In fact, these algorithms are implicitly based on the assumption that the positive and algebraic degrees of a certain estimated covariance sequence coincide. In this paper, we describe how to generate data with the property that this condition is not satisfied. Using these data we show through simulations that several subspace identification algorithms exhibit massive failure.
Full Text
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call