fracdim.m

用matlab实现利用统计混沌方法解决非线性系统时间序列预测的问题

function fracdim(fst,lst)
% The function 
%
%       fracdim(data);
%
% compute an estimation of the fractal dimension
% by the method of Grassberger and Proccacia.  
% The function opens a window which allows 
% to fine tune the LMS regression between
% the (log(r),log(N)) points.  
% The first arg <data> contains the data distribution 
% (one point or vector per row).  
% Don't use the function with 2 args!

global h1;
global h2;
global h3;
global h4;

global min;
global max;
global ptlist;

if nargin==1,
        %initialisation
        
        h0 = figure(...
                'position',[50,50,420,430],...
                'resize','off');
        
        h1 = uicontrol(...
                'style','text',...
                'position',[10,10,400,30],...
                'string','Please wait while computing ...');
        
        % sauver dans un fichier temporaire
        sv(fst,'temp.dat');
        
        % ligne a modifier en fonction du chemin vers fracdim.exe
        !e:\john\ucl\doc\cda\cpp\fracdim.exe temp.dat fracdim.dat
        
        % repecher les resultats dans le fichier temporaire
        ptlist = ld('fracdim.dat');
        
        % effacer le fichier temporaire
        !del temp.dat
        
        [i,j] = size(ptlist);
        
        min = 1;
        max = i;
        
        set(h1,'string',strcat('LMS Regression between points <',num2str(min),'> and <',num2str(max),'>.'));
        
        h2 = uicontrol(...
                'style','slider',...
                'position',[10,40,400,20],...
                'min',min,...
                'max',max,...
                'sliderstep',[1/(max-min),2/(max-min)],...
                'value',min,...
                'callback','global h1; global h2; global h3; set(h2,''value'',round(get(h2,''value''))); fracdim(get(h2,''value''),get(h3,''value''))');
        
        h3 = uicontrol(...
                'style','slider',...
                'position',[10,60,400,20],...
                'min',min,...
                'max',max,...
                'sliderstep',[1/(max-min),2/(max-min)],...
                'value',max,...
                'callback','global h1; global h2; global h3; set(h3,''value'',round(get(h3,''value''))); fracdim(get(h2,''value''),get(h3,''value''))');
        
        h4 = axes(...
                'units','pixels',...
                'position',[10,90,400,300],...
                'xtick',[],...
                'ytick',[]);
        
        fracdim(min,max);        
        
elseif nargin==2,
        %regression
        if fst < lst,
                X = [ones(lst-fst+1,1),ptlist(fst:lst,1)];
                y = ptlist(fst:lst,2);
                b = inv(X'*X)*X'*y;
                mqe = norm(y-X*b)/(lst-fst+1)
                mmqe = mqe/(lst-fst+1)
                plot(ptlist(:,1),ptlist(:,2),'r+');
                hold on;
                plot(X(:,2),y,'+');
                AX = axis;
                plot( [AX(1),AX(2)], [b(1)+AX(1)*b(2),b(1)+AX(2)*b(2)] );
                title(strcat('Fractal Dimension: ',num2str(b(2))));
                axis(AX);
                set(gca,'xtick',[],'ytick',[]);
                hold off;
                set(h1,'string',strcat('LMS Regression between points <',num2str(fst),'> and <',num2str(lst),'>.'));
        else
                set(h1,'string','First point must precede last point.');
        end
end;