The identification of parametric models from experimental data is a
fundamental activity among researchers and engineers in pure and
applied sciences. This work addresses the topic by examining, among
others, the following areas:
a [ choice of an appropriate model structure which allows the
estimation of all parameters;
a [ choice of a quality criterion for rating models;
a [ incorporation of prior knowledge and objectives and guarding
against possible outliers;
a [ optimization of the selected criterion and simple yet exact
evaluation of characteristics;
a [ evaluation of uncertainty in estimated parameters;
a [ design of experimental conditions for the collection of the
most pertinent information given prior constraints and
objectives.
Identification of Parametric Models deals with these questions
in a straightforward style while providing a global vision of the
methodology.
Suitable for engineers and researchers who practise mathematical
modelling from experimental data, graduate students who wish to
become acquainted with the field, this text will also be a valuable
resource for specialists in the field.
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