A simple one is the so-called "circle fitting" method. If you make a Nyquist plot of your measured data (i.e. plot imaginary part of the response against the real part), the section of the curve near the resonance is a circle, and you can fit a circle to the measured data and find the parameters from it.

Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year. Recall that in linear regression, our hypothesis is to denote the number of training examples. For the training set given above (note that this training set may also...

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