Abstract
A framework for data-based validation of nonlinear dynamical models is introduced. Simulations show how the methodology detects unmodelled nonlinearities where prior methods for nonlinear model validation fail. The methodology is easy to use and readily applied to MIMO systems. Furthermore, the method may answer the fundamental question of whether or not the underlying data warrants an exploration of nonlinear methods prior to any modelling efforts.
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