Experimental evidence showing that stochastic subspace identification methods may fail 1 1 This rese

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.

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