Editing System identification (section)

{{Short description|Statistical methods to build mathematical models of dynamical systems from measured data}}
{{Black-box}}
The field of '''system identification''' uses [[statistical method]]s to build [[mathematical model]]s of [[dynamical system]]s from measured data.<ref>{{Cite book|title=System identification|last1=Torsten|first1=Söderström|last2=Stoica|first2=P.|date=1989|publisher=Prentice Hall|isbn=978-0138812362|location=New York|oclc=16983523|author-link2=Peter Stoica}}</ref> System identification also includes the [[optimal design#System identification and stochastic approximation|optimal]] [[design of experiments]] for efficiently generating informative data for [[regression analysis|fitting]] such models as well as model reduction. A common approach is to start from measurements of the behavior of the system and the external influences (inputs to the system) and try to determine a mathematical relation between them without going into many details of what is actually happening inside the system; this approach is called '''[[Black box (systems)|black box]]''' system identification.