best-fit-curve

问题 I have 37 linear equations and 36 variables in the form of a matrix equation; A*X=B . The equations don't have an exact answer. I want to use Matlab least square method to find the answers with the least error. I am new to Matlab so any comments will help. Thank you 回答1: If A is of full rank, i.e. the columns of A are linearly independent, the least-squares solution of an overdetermined system of linear equations A * x = b can be found by inverting the normal equations (see Linear Least

问题 I want to fit a decaying exponential to the plotted data. I do NOT have the Curve Fitting or Optimization Toolboxes. x = [0 0.0036 0.0071 0.0107 0.0143 0.0178 0.0214 0.0250 0.0285 0.0321 0.0357 0.0392 0.0428 0.0464 0.0464]; y = [1.3985 1.3310 1.2741 1.2175 1.1694 1.1213 1.0804 1.0395 1.0043 0.9691 0.9385 0.9080 0.8809 0.7856 0.7856]; figure() plot(x,y,'*') How could I achieve this in MATLAB? 回答1: Assuming that you have Gaussian distributed errors between the input and output points, and