fann_create_standard(3) [php man page]

FANN_CREATE_STANDARD(3) 						 1						   FANN_CREATE_STANDARD(3)

fann_create_standard - Creates a standard fully connected backpropagation neural network

SYNOPSIS

       resource fann_create_standard (int  $num_layers, int  $num_neurons1, int  $num_neurons2, [int  $...])

DESCRIPTION

	Creates a standard fully connected backpropagation neural network.

	There  will  be  a  bias neuron in each layer (except the output layer), and this bias neuron will be connected to all neurons in the next
       layer. When running the network, the bias nodes always emits 1.

	To destroy a neural network use the fann_destroy(3) function.

PARAMETERS

	      o $num_layers
		- The total number of layers including the input and the output layer.

	      o $num_neurons1
		- Number of neurons in the first layer.

	      o $num_neurons2
		- Number of neurons in the second layer.

	      o $...
		- Number of neurons in other layers.

RETURN VALUES

	Returns a neural network resource on success, or FALSE on error.

SEE ALSO

       fann_create_standard_array(3), fann_create_sparse(3), fann_create_shortcut(3).

PHP Documentation Group 												   FANN_CREATE_STANDARD(3)

FANN_GET_ACTIVATION_STEEPNESS(3)					 1					  FANN_GET_ACTIVATION_STEEPNESS(3)

fann_get_activation_steepness - Returns the activation steepness for supplied neuron and layer number

SYNOPSIS

       float fann_get_activation_steepness (resource  $ann, int  $layer, int  $neuron)

DESCRIPTION

	Get the activation steepness for neuron number neuron in layer number layer, counting the input layer as layer 0.

	It is not possible to get activation steepness for the neurons in the input layer.

	The steepness of an activation function says something about how fast the activation function goes from the minimum to the maximum. A high
       value for the activation function will also give a more agressive training.

	When training neural networks where the output values should be at the extremes (usually 0 and 1, depending on the activation function), a
       steep activation function can be used (e.g. 1.0).

	The default activation steepness is 0.5.

PARAMETERS

	      o $ann
		-Neural network resource.

	      o $layer
		- Layer number

	      o $neuron
		- Neuron number

RETURN VALUES

	The activation steepness for the neuron or -1 if the neuron is not defined in the neural network, or FALSE on error.

SEE ALSO

       fann_set_activation_function(3),    fann_set_activation_steepness_layer(3),    fann_set_activation_steepness_hidden(3),	  fann_set_activa-
       tion_steepness_output(3), fann_set_activation_steepness(3).

PHP Documentation Group 											  FANN_GET_ACTIVATION_STEEPNESS(3)