function [y,fval]=fmaxbndn(f,a,b,n,OPTIONS,varargin) % FMAXBNDN(f,a,b,n,OPTIONS,varargin) % This is a crude way at trying to have a better chance of finding global maxima. % Suppose you have a function F(x_1,x_2,x_3,...x_n) that you want to maximize % as a function of its ith argument x_i over the intervall [a,b]. % You want to find a global maximum. What FMAXBNDN does is subdivide the interval % [a,b] into n intervalls, find a local maximum in each and then take the % global maximum of all. % Consider the example where you have four arguments, you want to maximize over % the third argument while the other arguments are x_1=1, x_2=2 and x_4=4. % Futhermore suppose that [a,b]=[0,1], that you want subdivision into 10 intervalls. % Then you would use the command % % fmaxbndn('F',0,1,10,1,2,[],4) % % Notice that an empty matrix [] was specified for the argument over which you want % to maximizae. n_parameters=length(varargin); parameter_string=''; for i=1:n_parameters if isempty(varargin{i}) parameter_string=[parameter_string 'x']; else parameter_string=[parameter_string num2str(varargin{i},15)]; end if i