Libfann2

> libfann_it

• struct fann, which represents an artificial neural network
• struct fann_train_data, which represent training data.
• fann_type, is the type used for the weights, inputs and outputs
• fann_connection, is the type which Describes a connection between two neurons and its weight

FANN Creation/Execution The FANN library is designed to be very easy to use.

1. fann_create_standard Creates a standard fully connected backpropagation neural network.
2. fann_create_standard_array Just like fann_create_standard, but with an array of layer sizes instead of individual parameters.
3. fann_create_sparse Creates a standard backpropagation neural network, which is not fully connected.
4. fann_create_sparse_array Just like fann_create_sparse, but with an array of layer sizes instead of individual parameters.
5. fann_create_shortcut Creates a standard backpropagation neural network, which is not fully connected and which also has shortcut connections.
6. fann_create_shortcut_array Just like fann_create_shortcut, but with an array of layer sizes instead of individual parameters.
7. fann_destroy Destroys the entire network and properly freeing all the associated memmory.
8. fann_run Will run input through the neural network, returning an array of outputs, the number of which being equal to the number of neurons in the output layer.
9. fann_randomize_weights Give each connection a random weight between min_weight and max_weight
10. fann_init_weights Initialize the weights using Widrow + Nguyen’s algorithm.
11. fann_print_connections Will print the connections of the ann in a compact matrix, for easy viewing of the internals of the ann.

• fann_print_parameters Prints all of the parameters and options of the ANN
• fann_get_num_input Get the number of input neurons.
• fann_get_num_output Get the number of output neurons.
• fann_get_total_neurons Get the total number of neurons in the entire network.
• fann_get_total_connections Get the total number of connections in the entire network.
• fann_get_network_type Get the type of neural network it was created as.
• fann_get_connection_rate Get the connection rate used when the network was created
• fann_get_num_layers Get the number of layers in the network
• fann_get_layer_array Get the number of neurons in each layer in the network.
• fann_get_bias_array Get the number of bias in each layer in the network.
• fann_get_connection_array Get the connections in the network.
• fann_set_weight_array Set connections in the network.
• fann_set_weight Set a connection in the network.
• fann_set_user_data Store a pointer to user defined data.
• fann_get_user_data Get a pointer to user defined data that was previously set with fann_set_user_data.
• fann_get_decimal_point Returns the position of the decimal point in the ann.
• fann_get_multiplier returns the multiplier that fix point data is multiplied with.