IDENTIFICATION OF THE STRUCTURE OF MULTIVARIABLE STOCHASTIC SYSTEMS

摘要

We consider the problem of identifying the structure of a multivariable linear system given observations on the input and output. Our approach involves the reduction of the dimensions of the input and output vectors, and is based on the application of principle components analysis to the frequency domain representations of the input and output processes, taking into account the "loss function" associated with the control of the system under study. Some results on tests of significance for the eigen values of a spectral density matrix are included.