Hello,
This limitation is alreay pointed out here :
http://bugzilla.scilab.org/show_bug.cgi?id=15756
S.
Le 15/01/2019 à 03:36, Federico Miyara a écrit :
Dear all,
This statement
a = {[%f, %t], {2; poly([3, 2],'v')}}
defines a cell array whose first element is a boolean row vector and
Dear all,
This statement
a = {[%f, %t], {2; poly([3, 2],'v')}}
defines a cell array whose first element is a boolean row vector and
whose second element in turn is another cell array.
Invoking a{1}(1) correctly returns the boolean value F.
But a{2}{1} does not return 2, as expected but an
Denis,
What I meant is that convergence is a limiting process. On average, as
the number of iterations rises you´ll be closer to the limit, bu there
is no guarantee that any single iteration will bring you any closer; it
may be a question of luck. Maybe (though it would require a proof, it
Thank you Frederico!
According to the page you refer to, the method seems to converge more rapidly
with this factor equal to the multiplicity of the root.
About overshoot, it is well known to occur for |x|^a where a <1. But for a>1,
the risk of overshoot with the Newton-Raphson method seems to
