Reduction of linear continuous-time multivariable systems by matching first- and second-order information

This paper considers the approximation of stable continuous-time multivariable linear systems from a finite number of Markov parameters and second-order information indexes. It is shown that, by properly choosing these indexes, it is possible to uniquely identify an input-output model of given order from an equal number of first- and second-order data.<
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