Let's say I am trying to validate a model. I have a signal from measurement and a signal from the simulation of the model. Simulation was done with the same initial and boundary conditions as measurement.
Now I want to compare two signals (e.g. temperatures of one modeled component). I want to have a number (or more than one) to quantify similarities in signals. The signals can be shifted in y-axis, have slightly different behaviours and can possibly have some delay in x-axis (time).
So far I tried some simply criterias like comparing max, min, first, last values and evaluating maximum differences in absolute value. Also I tested fitting percentage of fitting simulation signal into the neighbourhood of measured signal with given range.
I would like to have something more sophisticated. I tried Pearson correlation, but all coefficient are above 90% since the signals represent the same things.
I am looking for any ideas what statistical criteria or algorithms could be applied on this issue.