Hello,
I need an example how to apply Matlab's built in lsqr function to solve the following task.
let's say I have a sequence of square pulses which is transformed in the following way:
t = linspace(0, n, numel(s));
plot(t, s, 'Linewidth',2)
t2 = t * scale_factor + offset;
plot(t2, s, 'LineWidth',2)
Now if that previous transformation is unknown and I need to estimate scale_factor and offset i.e. my initial condition is actually only a plot data:
or my only inputs are:
T1 = [t1_n; ones(size(t1_n))];
T2 = [t2_n; ones(size(t2_n))];
How to use lsqr function to calculate scale_factor and offset. I know that for this particular case, I only need to points to calculate coefficients of line equation y = a*x+b, but in general, data can be noisy, so more points are needed and thus the obvious choise would be to use least square fitting.
Thank you!
P.S. I forgot to mention, I can solve this problem using the function lsqcurvefit, but I would like to see how lsqr can be applied.
