}}</ref> as key concept for quasi-LPVhigher order singular value (qLPV)decomposition controlof theoryfunctions. It transforms a function (which can be given via [[Closed-form expression|closed formulas]] or [[neural network]]s, [[fuzzy logic]], etc.) into TP function form if such a transformation is possible. If an exact transformation is not possible, then the method determines a TP function that is an approximation of the given function. Hence, the TP model transformation can provide a trade-off between approximation accuracy and complexity.<ref name=ykc01>{{cite journal
|author = D. Tikk, P.Baranyi, R. J. Patton
|title = Approximation Properties of TP Model Forms and its Consequences to TPDC Design Framework
