Question: Project 4: Model fitting and parameter estimation (0.5+1+3.5-5 points) write Matlab code for N=7 for algorithms (1), (2) and (3) below. In algorithm (3), use

Project 4: Model fitting and parameter estimation (0.5+1+3.5-5 points) write Matlab code for N=7 for algorithms (1), (2) and (3) below. In algorithm

Project 4: Model fitting and parameter estimation (0.5+1+3.5-5 points) write Matlab code for N=7 for algorithms (1), (2) and (3) below. In algorithm (3), use a maximum of 6 trials (2, 1), (3,5).(6,9), (12,7), (15,20), (18, 16), (22,30). Notes: Understand how to fit model to a data and find the best parameters. Understand this for the case of fitting N pixels at coordinates (Xi,Yi) for i 1 to N to a straight line using the following algorithms. 1. Linear Least squares: min(sum (Yi-Xi-b) 2) you need to initialize matrix A using the point data (2, 1), (3,5),(6,9), (12,7), (15,20), (18, 16), (22,30) It will be 22 1 with one row for each point. y is the column vector 30 and p = A \ y; (in MATLAB.) just, calculate p=[ m , b]. 2. Total linear least squares min (sum (aXi+bYi+C) 2) such that a 2+b 2 1 (get rho, theta) set up matrix A with i-th row containing xi-xbar yi-ybar

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