Abstract / truncated to 115 words (read the full abstract)

This thesis is focused on the basis function method for the identification of nonstationary processes. The first chapter describes a group of models that can be identified using the basis function method. The next chapter describes the basic version of the basis function method, including its algebraic and statistical properties. The following section introduces the local basis function (LBF) method: its properties are described and similarities and differences between LBF and the basic basis function method are highlighted. The main difference lies in the approach to estimation. The primary version of the basis function method provides estimates for the entire analysis interval. The analysis window is then shifted so that estimates can be found for ... toggle 5 keywords

system identification – nonstationary systems – local basis function method – regularization – adaptive identification

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