[libfann] 216/242: documantation etc.

[Christian Kastner]

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chrisk-guest pushed a commit to tag Version2_0_0
in repository libfann.

commit f4b66c7ca7c9ccbdc14235fa846e60c655132d50
Author: Steffen Nissen <lukesky at diku.dk>
Date:   Tue Dec 13 00:20:12 2005 +0000

    documantation etc.
---
 AUTHORS                 | 7 +++++--
 examples/simple_test.c  | 2 +-
 src/include/fann_data.h | 4 ++--
 3 files changed, 8 insertions(+), 5 deletions(-)

diff --git a/AUTHORS b/AUTHORS
index 791399c..cdd7ccd 100644
--- a/AUTHORS
+++ b/AUTHORS
@@ -27,11 +27,14 @@ Gil Megidish (gil at megidish.net)
 Joslwah (joslwah at gmail.com)
  - Optimised port for ppc64/altivec
 
-Søren Hauberg (hauberg _at_ gmail _dot_ com)
+Maur�cio Pereira Maia (mauricio at uaisol.com.br)
+ - Delphi Bindings
+
+S�ren Hauberg (hauberg _at_ gmail _dot_ com)
  - Bindings for GNU Octave
  
 Thomas Leibovici (thomas.leibovici at free.fr)
  - Momentum training
  
 Vincenzo Di Massa (hawk.it at_domain tiscali.it)
- - Python extension
\ No newline at end of file
+ - Python extension
diff --git a/examples/simple_test.c b/examples/simple_test.c
index 26ad225..6a2dddc 100644
--- a/examples/simple_test.c
+++ b/examples/simple_test.c
@@ -31,7 +31,7 @@ int main()
 	input[1] = 1;
 	calc_out = fann_run(ann, input);
 
-	printf("xor test (%f,%f) -> %f\n", input[0], input[1], *calc_out);
+	printf("xor test (%f,%f) -> %f\n", input[0], input[1], calc_out[0]);
 
 	fann_destroy(ann);
 	return 0;
diff --git a/src/include/fann_data.h b/src/include/fann_data.h
index c1d3d0d..f2afa23 100644
--- a/src/include/fann_data.h
+++ b/src/include/fann_data.h
@@ -102,10 +102,10 @@ static char const *const FANN_TRAIN_NAMES[] = {
    
 	The activation functions used for the neurons during training. The activation functions
 	can either be defined for a group of neurons by <fann_set_activation_function_hidden> and
-	<fann_set_activation_function_output> or it can be defined for a single neuron by <TODO>.
+	<fann_set_activation_function_output> or it can be defined for a single neuron by <fann_set_activation_function>.
 
 	The steepness of an activation function is defined in the same way by 
-	<fann_set_activation_steepness_hidden>, <fann_set_activation_steepness_output>
+	<fann_set_activation_steepness_hidden>, <fann_set_activation_steepness_output> and <fann_set_activation_steepness>.
    
    The functions are described with functions where:
    * x is the input to the activation function,

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