Optimization: principles and algorithms, by Michel Bierlaire
runGaussNewton.m
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1 %> \file
2 %> Run to illustrate the Gauss-Newton algorithm 14.1
3 %>
4 %> @note Calls \ref gaussNewton
5 %>
6 %> @ingroup Running
7 %> @ingroup chap14
8 %> @author Michel Bierlaire
9 %> @date Sat May 10 18:53:46 2014
10 
11 x0 = [0 ; 0] ;
12 [solution,iteres,niter] = gaussNewton('ex1401',x0,1.0e-4) ;
13 format short e
14 iteres(1:niter,:)
15 solution
16 format
17 niter
18 
function gaussNewton(in obj, in x0, in eps, in maxiter)
Applies Gauss-Newton algorithm to solve where .
Copyright 2015-2016 Michel Bierlaire