precision octave vs matlab

[michaelschmid1]

Hi all

First thanks for all the answers about my "global" problem... it works now...

but now the next problem..

I have programmed some parts of a neural network toolbox for Octave, like
the one of matlab. Some commands are working like "newff, train, sim" and
so on..
For the first training algorithm I decided to realize Levenberg-Marquardt.
Now if I make a comparison between the results of matlab and octave, there
are some small differences...
I searched for calculating errors but can't find anything. As far as I know,
both are using double-precision ... so where does this difference come from?
Is it really a calculating error or only a "rounding error"?

Octave output:
================
simOut =

 Columns 1 through 8:

  1.67883  2.05781  1.21596  2.82417  2.06661  2.00662  2.99825  1.65494

 Columns 9 through 16:

  1.65087  1.90819  1.90195  1.70142  2.61220  1.99405  0.99050  1.91911

 Columns 17 through 24:

  1.94686  0.93073  1.87499  1.75138  1.71708  2.21930  0.94781  2.02244

 Columns 25 through 30:

  2.01943  1.10781  2.02009  1.85863  2.71098  1.30415

matlab output:
==============

simOut =

  Columns 1 through 17 

    1.6767    1.9494    1.1277    2.7196    2.0406    1.9435    2.8583  
 1.6444    1.6437    1.8839    1.7769    1.6008    2.7412    1.9360    1.0998
   1.8426    1.8144

  Columns 18 through 30 

    1.0464    1.8657    1.7506    1.6612    2.1693    1.0655    1.8792  
 2.0094    1.0119    1.9947    1.8084    2.5923    1.2365

Of course both programmes have the same initial conditions...

I hope someone have similar experience with this kind of "trouble"
and that this person can tell me that I didn't make a calculation error..

Thanks 
Michel