Optimization: principles and algorithms, by Michel Bierlaire
gaussNewton.m File Reference

Algorithm 14.1: Gauss-Newton method. More...

Go to the source code of this file.

## Functions

function gaussNewton (in obj, in x0, in eps, in maxiter)
Applies Gauss-Newton algorithm to solve

where . More...

## Detailed Description

Algorithm 14.1: Gauss-Newton method.

Implementation of algorithm 14.1 of [1]

Note
Tested with runGaussNewton.m
Tested with runNeuralNetwork.m
Date
Sat Mar 21 16:51:49 2015

Definition in file gaussNewton.m.

## Function Documentation

 function gaussNewton ( in obj, in x0, in eps, in maxiter )

Applies Gauss-Newton algorithm to solve

where .

Parameters
 obj the name of the Octave function defining g(x) and its gradient matrix. It should return a vector of size m and a matrix of size n x m. x0 the starting point eps algorithm stops if . maxiter maximum number of iterations (Default: 100)
Returns
[solution,iteres,niter]
solution: local minimum of the function
iteres: sequence of iterates generated by the algorithm. It contains n+2 columns. Columns 1:n contains the value of the current iterate. Column n+1 contains the value of the objective function. Column n+2 contains the value of the norm of the gradient. It contains maxiter rows, but only the first niter rows are meaningful.
niter: total number of iterations