ctrical
network, whereas the gesv seems to be solid given the poking around I did a
little with it today. Over the weekend, I'll have more time to test it out
and solve. The code snippet I showed was for a Shannon Switching game, to
just try out the Laplacian etc. I'll let you know how it work
Actually I just noticed there is a fast solver in Lapack for solving Ax=b.
This is all I need - thanks!
load 'math/lapack/gesv'
m1=: ?.4 3$30
gesv_jlapack_ m;m1 NB. solves m * x = m1
Brian Babiak MD
https://drbabiak.com/ <http://drbabiak.com>
paypal: *http
Thanks for the help everyone. LAPACK is very useful. I also appreciate the
Rosetta code mesh. It's interesting how many choices were made the same. I
appreciate the help on this!
Brian Babiak MD
https://drbabiak.com/ <http://drbabiak.com>
paypal: *http://www.paypal.me/BrianBabi
00
0 _2 _2 0 0 _2 8 _2
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00
0 0 _2 0 0 0 _2 4
-/ . * a
_8.08478e26
%. a
|domain error
| %.a
Brian Babiak MD
https://drbabiak.com
167 Ridgecrest Rd.
Ithaca NY 14850 – 9449
(607) 379 – 1335
y end.
while. i:j
end.
j=. 0
i=. >:i
end.
mat
)
D=: 3 : 0
diag=. (2$netsz)$ 1,netsz#0 [ netsz=. *:BOARDSZ [ colsum=. +/y [ y=. A y
r=. colsum*diag
)
L=: D-A NB. the Laplacian
NB. %. Laplacian or . (dot) for Laplaci
ll answers were helpful. Thanks!
Brian Babiak MD
https://drbabiak.com/ <http://drbabiak.com>
On Mon, Jul 24, 2017 at 10:02 PM, 'Jon Hough' via Programming <
programm...@jsoftware.com> wrote:
> You can definitely create Artificial Neural Nets in J. I think it is
> pro
mples or
information about neural nets and supervised learning in j would be
appreciated!
Brian Babiak MD
https://drbabiak.com/ <http://drbabiak.com>
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