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A new recursive orthogonal estimation algorithm is derived which updates both the model structure and the parameters of nonlinear models on-line. Techniques developed for on-line modification of the structure of linear models are not generally suitable when nonlinear systems are considered, because the vector-shift properties no longer hold for nonlinear models and the demands of real-time processing...
A new algorithm which provides adaptive model selection and estimation on-line is derived based on the polynomial nonlinear ARMAX model (NARMAX). The algorithm uses rectangular windowing regression procedures where the forgetting factor is unity within a sliding data window. Variations in the model structure, or which terms are in the model, and the parameter estimates are tracked by using a sliding...
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