nonlinear transformation between two sets of data points

I am looking for an easy approach to find the best fit between two sets of datapoints. I know that there is a non-linear transformation between the two datasets, and I want to find a scale factor and an exponential component which best transforms the first datapoints (moving data) to the first datapoints (fixed data).

I have read about system identification toolbox and transfer functions, but I saw that it mostly used for extracting noise from the data and not the transformation between two sets of data. I was wondering if somebody can give me a clue of what is an easy and robust approach to use for this problem.

Answer 1

[Star Strider]

The question is a bit ambiguous. If ‘fixed data’ is an input to the system, and ‘moving data’ is the output, the ssest function will produce a system that describes (in matrix form) a set ot linear differential equations that models the process that created the resulting ‘moving data’.from ‘fixed data’.

See the examples in the documentation I linked to, to see if they describe the problem to be solved. If they do not, please describe the problem in more detail.

.