Validation of an estimated model is not a trivial task because it depends on the purpose of the model,
which usually defines the most important features of the
model. Thus, in a validation process, the use of diverse tools
that exploit different domains is recommended. Here, with
this aim, a scale for model validation is proposed that combines the Normalized Root Mean Square Error (NRMSE)
with two new indices: the coherence-based index and the
fourth-order cross-cumulant index. The proposed scale was
used for the validation of three models: the Logistic Map,
the Duffing–Ueda oscillator, and the Buck converter. The
results demonstrated that the proposed model validation scale
produces a more complete validation process that takes into
account both time and frequency information and provides
robustness against Gaussian noise
