Doubt on data of a SISO system
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Hello all,
How can I know if the relationship between these data is linear or nonlinear?
u=[0.158 0.105 0.158 0.158 0.158 0.158 0.105 0.158 0.105 0.105 0.158 0.158 0.158 0.158 0.211 0.211 0.158 0.105 0.158 0.211 0.158 0.105 0.105 0.105 0.158 0.158 0.158 0.158 0.158 0.158]
y=[0.760 0.759 0.757 0.759 0.763 0.763 0.763 0.767 0.770 0.771 0.770 0.770 0.766 0.758 0.758 0.758 0.757 0.757 0.756 0.753 0.750 0.749 0.749 0.754 0.756 0.756 0.756 0.756 0.755 0.755]
Where, u is the input and y is the output, and 0.158 really indicate the same location. Consider that there are no errors in the measured signals.
In fact, I want to know if the relationship between u and y is linear or nonlinear.
Does anyone have any suggestions?
Thanks.
[Information merged from answer]
I found this paper:
S.A. Billings, W.S.F. Voon (1983), Structure detection and model validity tests in the identification of nonlinear systems, IEE Proceedings, Vol. 130, No. 4, JULY 1983.
In Section 4 the authors use a high-order correlation function applied to the response signal performed in a linear identification. Then, if the result is within the confidence inteval of 95% means that the system is linear.
How can I implement the function described by Billings e Voon in matlab? If I'm not mistaken ,I will need to use a FIR model, is not it?
Can you help me with this?
Thanks
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Answers (1)
Walter Roberson
on 27 Jan 2012
If one accepts that there are errors in the measurement of the values, then you cannot prove that the relationship is non-linear: the best you could do would be to calculate an error term.
The multiple occurrences of 0.158 in u (or is it x?): are those intended to represent the exact same location, or are they intended to indicate locations that are certainly different but are the same to within 3 decimal places?
6 Comments
Walter Roberson
on 29 Jan 2012
Emanual, I have not read that paper, and I have not studied system identification and I have not studied digital filters. I would have to do a fair bit of reading to figure out how to implement an algorithm such as that. I do not have the resources for doing that.
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