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Abstract
A survey is presented of the existing literature on the identification of linear multivariable discrete-time systems from input-output data. The existing algorithms are classified according to the model used in the identification problem and a comparison is made between the different models. Emphasis is given to on-line algorithms for the identification from noisy data. Some new ideas for solving the problem are also presented,