Brief paper: On the uniqueness of maximum likelihood identification

Authors:
T Söderström
Affiliations:
-
Venue:
Automatica (Journal of IFAC)
Year:
1975

Citing 4
Cited 5

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On the problem of ambiguities in maximum likelihood identification

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Convergence properties of the generalised least squares identitication method

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Brief paper: Some properties of the output error method

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Abstract

The maximum likelihood method of identification is a powerful tool for obtaining mathematical models of dynamic processes. To apply this method a loss function has to be minimized. The aim of the paper is an investigation of the local minimum points of this loss function for a common structure of a general form. If the loss function has more than one local minimum point, numerical problems can occur during the minimization. Sufficient conditions are given for the existence of a unique stationary point, which then also gives the desired global minimum. It is also shown by counter-examples that there are systems without peculiarities, which have more than one local minimum point of the loss function.