Abstract
A key problem in system identification is the determination of the correct model structure. For example, single-input/single output systems which are characterised by a discrete transfer function model (e.g. Astrom’s formulation) have a system structure which is determined by the respective orders of the regression polynomials. The various model order testing procedures are compared under the classification (i) Subjective methods with probability measure, (ii) Subjective methods with no probability measure, and (iii) Objective methods. In addition a distinction is made between methods derived for systems with dependent and independent observations. The merits of objective procedures are stressed by a number of numerical examples.
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