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Authors
Lennart Ljung

Identifier
10.3182/20060329-3-AU-2901.00085

Index Terms
nonlinear system identification,neural networks,nonlinear models

Abstract
Identification of nonlinear systems is a very extensive problem, with roots and branches in several diverse fields. It is not possible to survey the area in a short text. The current presentation gives a subjective view on some essential features in the area. These concern a classification of methods, the use of different shades of grey in models, and some overall issues like bias-variance trade-offs, data sparseness and the peril of local minima.

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