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Comment:Now ceases if |error|<criterion
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SHA3-256: 3300f687234780f3c60f44e4093e6e235939bbba57555398c509e6e3f7286289
User & Date: gawthrop@users.sourceforge.net on 1999-12-08 06:42:31
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Context
1999-12-13
22:26:03
*** empty log message *** check-in: d380c79cb3 user: gawthrop@users.sourceforge.net tags: origin/master, trunk
1999-12-08
06:42:31
Now ceases if |error|<criterion check-in: 3300f68723 user: gawthrop@users.sourceforge.net tags: origin/master, trunk
06:32:40
Iterations now counts function evaluations - so minimum is 2. check-in: e506e8acbd user: gawthrop@users.sourceforge.net tags: origin/master, trunk
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Modified mttroot/mtt/bin/trans/m/mtt_optimise.m from [a05c50834e] to [261e38eb89].

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  error_old = inf;
  error=1e50;
  theta = theta_0;
  Theta = [];
  Error = [];
  Y = [];
  iterations = 0;
  while (abs(error_old-error)>criterion)&&(iterations<max_iterations)
    iterations = iterations + 1;
    error_old_old = error_old;
    error_old = error;
    eval(sprintf("[t,y,y_theta] = \
	mtt_s%s(system_name,theta,free);",method)); # Simulate system

    if View








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  error_old = inf;
  error=1e50;
  theta = theta_0;
  Theta = [];
  Error = [];
  Y = [];
  iterations = 0;
  while (abs(error_old-error)>criterion)&&(abs(error)>criterion)&&(iterations<max_iterations)
    iterations = iterations + 1;
    error_old_old = error_old;
    error_old = error;
    eval(sprintf("[t,y,y_theta] = \
	mtt_s%s(system_name,theta,free);",method)); # Simulate system

    if View
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    if error<(error_old+criterion) # Save some diagnostics
      Error = [Error error];	# Save error
      Theta = [Theta theta];	# Save parameters
      Y = [Y y];		# Save output
    endif

    ## Update the estimate if we are not done yet.
    if (abs(error_old-error)>criterion)&&(iterations<max_iterations)
      if error>(error_old+criterion) # Reduce step size and try again
        factor = 10;
	disp(sprintf("%2.2f*step",alpha));
	error = error_old;	# Go back to previous error value
	error_old = inf;	# Don't let it think its converged
	theta(free) = theta(free)  + step; # Reverse step
	step = alpha*step;	# new stepsize








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    if error<(error_old+criterion) # Save some diagnostics
      Error = [Error error];	# Save error
      Theta = [Theta theta];	# Save parameters
      Y = [Y y];		# Save output
    endif

    ## Update the estimate if we are not done yet.
    if (abs(error_old-error)>criterion)&&(abs(error)>criterion)&&(iterations<max_iterations)
      if error>(error_old+criterion) # Reduce step size and try again
        factor = 10;
	disp(sprintf("%2.2f*step",alpha));
	error = error_old;	# Go back to previous error value
	error_old = inf;	# Don't let it think its converged
	theta(free) = theta(free)  + step; # Reverse step
	step = alpha*step;	# new stepsize
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