/[gsl]/gsl/doc/multiroots.texi
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revision 1.1.1.2 by bjg, Sun Sep 8 09:54:49 2002 UTC revision 1.1.1.2.8.1 by bjg, Sun Jul 20 15:02:50 2003 UTC
# Line 647  internal scaling. Line 647  internal scaling.
647    
648  @deffn {Solver} gsl_multiroot_fsolver_dnewton  @deffn {Solver} gsl_multiroot_fsolver_dnewton
649    
650  @cindex Discrete newton algorithm for multidimensional roots  @cindex Discrete Newton algorithm for multidimensional roots
651  @cindex Newton algorithm, discrete  @cindex Newton algorithm, discrete
 @cindex Discrete Newton algorithm for nonlinear systems  
652    
653  The @dfn{discrete Newton algorithm} is the simplest method of solving a  The @dfn{discrete Newton algorithm} is the simplest method of solving a
654  multidimensional system.  It uses the Newton iteration  multidimensional system.  It uses the Newton iteration
# Line 1002  The addition of derivative information t Line 1001  The addition of derivative information t
1001  not make any significant difference to its behavior, since it able to  not make any significant difference to its behavior, since it able to
1002  approximate the Jacobian numerically with sufficient accuracy.  To  approximate the Jacobian numerically with sufficient accuracy.  To
1003  illustrate the behavior of a different derivative solver we switch to  illustrate the behavior of a different derivative solver we switch to
1004  @code{gnewton}. This is a traditional newton solver with the constraint  @code{gnewton}. This is a traditional Newton solver with the constraint
1005  that it scales back its step if the full step would lead "uphill". Here  that it scales back its step if the full step would lead "uphill". Here
1006  is the output for the @code{gnewton} algorithm,  is the output for the @code{gnewton} algorithm,
1007    

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