Lorenz混沌的lyapunov指数谱的正确代码

% Chapter 13 - Three-Dimensional Autonomous Systems and Chaos.
% Programs_13d - Lyapunov exponents of the Lorenz system.
% Copyright Birkhauser 2004. Stephen Lynch.

% Special thanks to Vasiliy Govorukhin for allowing me to use his M-files.
% For continuous and discrete systems see the Lyapunov Exponents Toolbox of
% Steve Siu at the mathworks/matlabcentral/fileexchange.

% Reference.
% A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano, "Determining Lyapunov Exponents from a Time Series," Physica D,
% Vol. 16, pp. 285-317, 1985.
% You must read the above paper to understand how the program works.

% Lyapunov exponents for the Lorenz system below are: 
% L_1 = 0.9022, L_2 = 0.0003, L_3 = -14.5691 when tend=10,000.

function [Texp,Lexp]=lyapunov(n,rhs_ext_fcn,fcn_integrator,tstart,stept,tend,ystart,ioutp);

n=3;rhs_ext_fcn=@lorenz_ext;fcn_integrator=@ode45;
tstart=0;stept=0.5;tend=300;
ystart=[1 1 1];ioutp=10;
n1=n; n2=n1*(n1+1);

%  Number of steps.
nit = round((tend-tstart)/stept);

% Memory allocation.
y=zeros(n2,1); cum=zeros(n1,1); y0=y;
gsc=cum; znorm=cum;

% Initial values.
y(1:n)=ystart(:);

for i=1:n1 y((n1+1)*i)=1.0; end;

t=tstart;

% Main loop.
for ITERLYAP=1:nit
% Solutuion of extended ODE system. 
  [T,Y] = feval(fcn_integrator,rhs_ext_fcn,[t t+stept],y);  
  t=t+stept;
  y=Y(size(Y,1),:);

  for i=1:n1 
      for j=1:n1 y0(n1*i+j)=y(n1*j+i); end;
  end;

% Construct new orthonormal basis by Gram-Schmidt.

  znorm(1)=0.0;
  for j=1:n1 znorm(1)=znorm(1)+y0(n1*j+1)^2; end;

  znorm(1)=sqrt(znorm(1));

  for j=1:n1 y0(n1*j+1)=y0(n1*j+1)/znorm(1); end;

  for j=2:n1
      for k=1:(j-1)
          gsc(k)=0.0;
          for l=1:n1 gsc(k)=gsc(k)+y0(n1*l+j)*y0(n1*l+k); end;
      end;
 
      for k=1:n1
          for l=1:(j-1)
              y0(n1*k+j)=y0(n1*k+j)-gsc(l)*y0(n1*k+l);
          end;
      end;

      znorm(j)=0.0;
      for k=1:n1 znorm(j)=znorm(j)+y0(n1*k+j)^2; end;
      znorm(j)=sqrt(znorm(j));

      for k=1:n1 y0(n1*k+j)=y0(n1*k+j)/znorm(j); end;
  end;

%  Update running vector magnitudes.

  for k=1:n1 cum(k)=cum(k)+log(znorm(k)); end;

%  Normalize exponent.

  for k=1:n1 
      lp(k)=cum(k)/(t-tstart); 
  end;

% Output modification.

  if ITERLYAP==1
     Lexp=lp;
     Texp=t;
  else
     Lexp=[Lexp; lp];
     Texp=[Texp; t];
  end;
    
  for i=1:n1 
      for j=1:n1
          y(n1*j+i)=y0(n1*i+j);
      end;
  end;

end;

% Show the Lyapunov exponent values on the graph.
str1=num2str(Lexp(nit,1));str2=num2str(Lexp(nit,2));str3=num2str(Lexp(nit,3));
plot(Texp,Lexp);
title('Dynamics of Lyapunov Exponents');
text(235,1.5,'\lambda_1=','Fontsize',10);
text(250,1.5,str1);
text(235,-1,'\lambda_2=','Fontsize',10);
text(250,-1,str2);
text(235,-13.8,'\lambda_3=','Fontsize',10);
text(250,-13.8,str3);
xlabel('Time'); ylabel('Lyapunov Exponents');
% End of plot

function f=lorenz_ext(t,X);
%
% Values of parameters.
SIGMA = 10; R = 28; BETA = 8/3;

x=X(1); y=X(2); z=X(3);

Y= [X(4), X(7), X(10);
    X(5), X(8), X(11);
    X(6), X(9), X(12)];

f=zeros(9,1);

%Lorenz equation.
f(1)=SIGMA*(y-x);
f(2)=-x*z+R*x-y;
f(3)=x*y-BETA*z;

%Linearized system.
 Jac=[-SIGMA, SIGMA,     0;
         R-z,    -1,    -x;
           y,     x, -BETA];
  
%Variational equation.   
f(4:12)=Jac*Y;

%Output data must be a column vector.

% End of Programs_13d.