📄 lorenzeq.m
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function OUT=lorenzeq(t,X)%LORENZEQ Lorenz equation % (a 3rd-order continuous autonomous system):%% dx/dt = SIGMA*(y - x)% dy/dt = RHO*x - y -x*z% dz/dt= x*y - BETA*z%% In this demo, SIGMA = 16, RHO = 45.92, BETA = 4% Initial conditions: x(0) = 1, y(0) = 1, z(0) = 1;% Reference values: LE1 = 1.497, LE2 = 0.00, LE3 = -22.46, LD = 2.07%% The reference values are from the following references:%% [1] 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.%% [2] Keith Briggs, "An Improved Method for Estimating Liapunov% Exponents of Chaotic Time Series," Phys. Lett. A, Vol. 151,% pp. 27-32, Nov. 1990.% by Steve Wai Kam SIU, Jun. 29, 1998.%PARAMETERSSIGMA = 16;RHO = 45.92;BETA = 4;%Rearrange input data in desired format%Note: the input data is a column vectorx=X(1);y=X(2);z=X(3);Q=[X(4), X(7), X(10); X(5), X(8), X(11); X(6), X(9), X(12)];%Lorenz equationdx=SIGMA*(y-x);dy=-x*z+RHO*x-y;dz=x*y-BETA*z;DX1=[dx;dy;dz]; %Output data%Linearized system J=[-SIGMA, SIGMA, 0; RHO-z, -1, -x; y, x, -BETA]; %Variational equation F=J*Q;%Output data must be a column vectorOUT=[DX1; F(:)];
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