📄 sethelp.m
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%==========================================================================% PARAMETERS SETTING%==========================================================================%% In the parameter setting window, users can specify desired parameters.% When finish entering parameters, press the "OK" button to save the% parameters and return to the main window.%%% 1. OUTPUT OPTIONS%% Users can save the calculated results in a file when the "Output File"% checkbox is checked. The users can choose save either the Lyapunov% exponents or Lyapunov dimension or save both by checking the corres-% ponding checkboxes. The precision pop-up menu allows the users to% specify the precision of the data printed in the file. Note that% the results will be printed EVERY ITERATION, thus will slow down the % overall calculation speed.%%% 2. INTEGRATION PARAMETERS%% a) ODE function is the name of the M-file that describes the ODEs% and variational equation of the concerned system. For instance,% the Lorenz system's ODE function is saved in LORENZEQ.M, so we% have to enter LORENZEQ in the "ODE function" edit box.%% b) There are 6 integration methods for users to choose from. "Discrete% map" is for discrete systems while the others are for continuous% systems. Details of the integration methods for continuous systems% are listed in the above pop-up menu.%% c) For continuous systems, users have to specify the initial time,% time step, final time, relative tolerance as well as absolute% tolerance. For discrete systems, the initial time must be zero and% the time step must be unity.%% The default relative and absolute tolerances are 1E-5. For simpli-% fication, the same absolute tolerance is used for all state vari-% ables of the ODEs though MATLAB's integration functions allow users% to specify the absolute tolerance of each state variable. The% relative and absolute tolerances are not applicable to discrete% maps, so a zero is displayed. Moreover, for discrete systems, the% final time must be an integer since it is the total number of steps% taken in the calculation.%% d) The number of initial conditions must be equal to the total number% of state variables of the system. Users need not to specify the% initial conditions for the variational equation since the program% can generate the initial conditions for the variational equation as% long as the users provide the correct number of linearized ODEs.%% In order to obtain correct results, users should provide suitable% initial conditions. Some initial conditions will drive the system% into a fix point. In this case, one or more Lyapunov exponents% will stay on their initial values and never be changed, so it must% be avoided. Note: for non-autonomous systems, one of the Lyapunov% exponents (LEs) is always zero and constant, this is expected and% should not be considered as the above case as long as the other% LEs are not constant.%% Some complex systems, especially high dimensional systems, have% several or more basins of attractions, so two sets of initial % conditions in different basins of attractions will result in two% different sets of Lyapunov exponents. Therefore, the users should% select the initial conditions carefully.%% e) The number of linearized ODEs is equal to the total number of% elements in the Jacobian matrix. Since the Jacobian matrix is% a squre matrix, the number must be the square of an integer.% For the Lorenz system, the number of linearized ODEs is 9 (3 x 3).% This number is required in generating the initial conditions for% the variational equation.%%% 3. PLOTTING OPTIONS% % The program allows the users to control the drawing frequency. % Updating the plot too frequent will result in a longer calculation% time while displaying the results not often enough may affect the% users to decide whether the results are convergent or not. Thus,% the users should make a compromise between the speed of calculation% and the convergence of results.%% Moreover, users can add x-axis, y-axis labels and title on the% figure. They can also choose the line color for plotting.%%% 4. ITERATION PARAMETERS%% Due to transient behavior, the determined results may be inaccurate% if the integration time is not long enough. Therefore, it is better% let the system to evolve some time before calculating the Lyapunov% exponents. Note that this transient time is in terms of ITERATIONS% but not time steps (here, ITERATION means one iteration in determin-% ing the Lyapunov exponents, it may be more than one time step).% % The program updates the Lyapunov exponents every k time steps (one% ITERATION). k should neither be chosen too small nor too large% since a too small k will result in overheads while a too large k% may cause overflow in the calculation (as the distances between% nearby trajectories increase exponentially). When an NAN or% INF becomes one of the results, this indicates that the overflow% has occurred.%% See also: ODE45, ODE23, ODE115, ODE23S, ODE15S, ODEFILE, README, % and LETHELP%%% by Steve W. K. SIU, July 5, 1998.help sethelp
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