In this paper, two approaches, for the estimation of matrices A and C in CV A-type subspace identification algorithms are compared and the differences between the two obtained estimates are analysed. One of the methods, "least squares" based, was proposed in the original CVA algorithm. The other method, inspired in the techniques of the classical Realization Theory and proposed by Verhaegen, is far more efficient. Therefore, although tRe two methods produce two different estimates, a replacement is proposed and an expression for correction of the estimates is obtained, in order to reduce the loss of accuracy.
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