In this paper a unified theory is presented for system identification in structural dynamics using recursive frequency-domain filters. Output error, equation error, and instrumental variable (I. V.) filters are developed as special cases. Parameter estimates are extracted from noisy simulated data from a multi-degree-of-freedom system. The equation error filter is strongly convergent but is prone to asymptotic bias error in the presence of measurement noise. An I. V. filter is developed in order to overcome the bias problem while maintaining the desirable convergence properties of the equation error approach.

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