Rational model identification using an extended least-squares algorithm

Abstract
A new least-squares-based parameter-estimation algorithm is derived for nonlinear systems which can be represented by a rational model defined as the ratio of two polynomial expansions of past system inputs, outputs and noise. Simulation results are included to illustrate the performance of the new algorithm.

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