fsom/fsom.h

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/*
* =====================================================================================
*
* Filename: neural_som.h
*
* Description: Header file for neural_som mini-library
*
* Version: 0.1
* Created: 15/10/2010 15:31:50
* Revision: none
* Compiler: gcc
*
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* Author: BlackLight (http://blacklight.gotdns.org), <blacklight@autistici.org>
* Contributor: evilsocket (http://www.evilsocket.net), <evilsocket@gmail.com>
* Licence: BSD-3
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*
* =====================================================================================
*/
/*
* Copyright (c) 2010, Fabio "BlackLight" Manganiello
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the the developers nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE DEVELOPERS BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
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#ifndef __NEURAL_SOM_H
#define __NEURAL_SOM_H
#include <stddef.h>
#include <time.h>
#define TAYLOR_LAMBERT_ELEMENTS 1001
#define TAYLOR_LAMBERT_LAST_ELEMENT 1000
#ifndef INLINE
# define INLINE __inline__ __attribute__((always_inline))
#endif
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typedef struct {
double output;
double input;
struct som_synapsis_s **synapses;
size_t synapses_count;
} som_neuron_t
__attribute__ ((aligned));;
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typedef struct som_synapsis_s {
som_neuron_t *neuron_in;
som_neuron_t *neuron_out;
double weight;
} som_synapsis_t
__attribute__ ((aligned));
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typedef struct {
som_neuron_t **neurons;
size_t neurons_count;
} som_input_layer_t
__attribute__ ((aligned));
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typedef struct {
som_neuron_t ***neurons;
size_t neurons_rows;
size_t neurons_cols;
} som_output_layer_t
__attribute__ ((aligned));
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typedef struct {
som_input_layer_t *input_layer;
som_output_layer_t *output_layer;
double T_learning_param;
time_t serialization_time;
double alphas[TAYLOR_LAMBERT_ELEMENTS];
double mus[TAYLOR_LAMBERT_ELEMENTS];
} som_network_t
__attribute__ ((aligned));
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void som_network_destroy ( som_network_t* );
void som_set_inputs ( som_network_t*, double* );
void som_train ( som_network_t*, double**, size_t, size_t );
void som_serialize ( som_network_t*, const char* );
void som_init_weights ( som_network_t*, double**, size_t );
double som_get_best_neuron_coordinates ( som_network_t*, size_t*, size_t* );
som_network_t* som_deserialize ( const char* );
som_network_t* som_network_new ( size_t, size_t, size_t );
#endif