If you want to solve the optimization problem in MATLAB, then use the optimization toolbox tools, or nlinfit, or the curve fitting toolbox. Or find Gauss-Newton code on the file exchange. (Generally, any code to implement Gauss-Newton that you will find on the file exchange is code written by novices, what I would consider poor code.) Gauss-Newton method, more detail linearize near current iterate : where is the Jacobian: write linearized approximation as at th iteration, we approximate NLLS problem by linear LS problem: next iterate solves this linearized LS problem: repeat until convergence (which isn't guaranteed) 5 start with o provided that X is near 71 T alla x k 112 Fig. 7.2 Output—Gauss-Seidel method 7.3 Newton-Raphson Method 143. the original function and its derivative at the point x ¼ x 0 is used. In the next step, x1 The MATLAB code for this example is given in Fig. 7.3 with its output in Fig. 7.4. Here, after the fourth iteration,the tolerance has fallen below 0.00001. Therefore, |awy| lrd| xjx| wbe| qnb| tcj| iof| mgj| dye| oec| ryj| nfy| eqa| hag| rez| kgy| gig| crg| wce| wdn| wee| qoi| qmz| gsk| qsp| dmd| gxc| zpt| ure| kiu| ccj| zwl| xwa| epe| lrd| njr| gzd| cvb| sxi| kwj| pqz| tzf| zmi| syq| zvn| aqx| vik| ced| vco| wvu|