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Abstract The identification of a non-linear output-affine difference equation model is considered. An orthogonal least-squares algorithm is derived that can determine the term to regress upon, detect significant terms in the model expansion, and provide the final parameter estimates. It is shown that the orthogonal property of the algorithm results in a particularly simple estimation routine and simulated examples are included to illustrate the techniques.
Billings et al. (Fri,) studied this question.