User choices and model validation in system identification using nonlinear Wiener models

Abstract The issue of user choices in system identification is of paramount importance. This paper therefore attempts to systematically discuss user choices for algorithms based on a specific class of nonlinear models, namely the Wiener model. In particular, the paper addresses model selection, user choices in algorithms, sampling, input signal selection as well as disturbance handling and modelling errors. Validation methods applicable to Wiener type systems are also discussed. A new method based on mean residual analysis is presented. Parts of the discussion of the paper applies also to general nonlinear system identification.

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