Skip to Main Content
Practical Neural Network Recipies in C++
book

Practical Neural Network Recipies in C++

by Masters
June 2014
Intermediate to advanced content levelIntermediate to advanced
493 pages
20h 30m
English
Morgan Kaufmann
Content preview from Practical Neural Network Recipies in C++
428
Appendix
void
1n
norm
(
double *1nput
.
double *normfac
.
double *synth
)
1nt winner
(
double *1nput
.
double *normfac
.
double *synth
) ;
void
wt
norm
(
double
*w ) ;
void zero weights
() ;
double *out coefs
//
nout
*
(n1n+l) weights
CONST.H System
and
program limitation constants
This also contains typedefs, structs.
et
cetera.
* See the
comment above
BAD
COMPILER.
•A·
* The
//1
f above MALLOC controls whether
or not the
diagnostic memory
*
allocation routines
are
used. They only slow things
a
tiny
bit.
*
RANDMAX
may be
system dependent.
See
your documentation.
•A·
* MAX
INPUTS.
MAX
HIDDEN
and MAX
OUTPUTS
are
primarily
to
simplify
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Neural Networks with Keras Cookbook

Neural Networks with Keras Cookbook

V Kishore Ayyadevara
Scientific Computing with Python 3

Scientific Computing with Python 3

Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier
Mastering Java Machine Learning

Mastering Java Machine Learning

Uday Kamath, Krishna Choppella

Publisher Resources

ISBN: 9780080514338