123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110 |
- /*
- * GENANN - Minimal C Artificial Neural Network
- *
- * Copyright (c) 2015, 2016 Lewis Van Winkle
- *
- * http://CodePlea.com
- *
- * This software is provided 'as-is', without any express or implied
- * warranty. In no event will the authors be held liable for any damages
- * arising from the use of this software.
- *
- * Permission is granted to anyone to use this software for any purpose,
- * including commercial applications, and to alter it and redistribute it
- * freely, subject to the following restrictions:
- *
- * 1. The origin of this software must not be misrepresented; you must not
- * claim that you wrote the original software. If you use this software
- * in a product, an acknowledgement in the product documentation would be
- * appreciated but is not required.
- * 2. Altered source versions must be plainly marked as such, and must not be
- * misrepresented as being the original software.
- * 3. This notice may not be removed or altered from any source distribution.
- *
- */
- #ifndef __GENANN_H__
- #define __GENANN_H__
- #include <stdio.h>
- #ifdef __cplusplus
- extern "C" {
- #endif
- #ifndef GENANN_RANDOM
- /* We use the following for uniform random numbers between 0 and 1.
- * If you have a better function, redefine this macro. */
- #define GENANN_RANDOM() (((double)rand())/RAND_MAX)
- #endif
- typedef double (*genann_actfun)(double a);
- typedef struct genann {
- /* How many inputs, outputs, and hidden neurons. */
- int inputs, hidden_layers, hidden, outputs;
- /* Which activation function to use for hidden neurons. Default: gennann_act_sigmoid_cached*/
- genann_actfun activation_hidden;
- /* Which activation function to use for output. Default: gennann_act_sigmoid_cached*/
- genann_actfun activation_output;
- /* Total number of weights, and size of weights buffer. */
- int total_weights;
- /* Total number of neurons + inputs and size of output buffer. */
- int total_neurons;
- /* All weights (total_weights long). */
- double *weight;
- /* Stores input array and output of each neuron (total_neurons long). */
- double *output;
- /* Stores delta of each hidden and output neuron (total_neurons - inputs long). */
- double *delta;
- } genann;
- /* Creates and returns a new ann. */
- genann *genann_init(int inputs, int hidden_layers, int hidden, int outputs);
- /* Creates ANN from file saved with genann_write. */
- genann *genann_read(FILE *in);
- /* Sets weights randomly. Called by init. */
- void genann_randomize(genann *ann);
- /* Returns a new copy of ann. */
- genann *genann_copy(genann const *ann);
- /* Frees the memory used by an ann. */
- void genann_free(genann *ann);
- /* Runs the feedforward algorithm to calculate the ann's output. */
- double const *genann_run(genann const *ann, double const *inputs);
- /* Does a single backprop update. */
- void genann_train(genann const *ann, double const *inputs, double const *desired_outputs, double learning_rate);
- /* Saves the ann. */
- void genann_write(genann const *ann, FILE *out);
- double genann_act_sigmoid(double a);
- double genann_act_sigmoid_cached(double a);
- double genann_act_threshold(double a);
- double genann_act_linear(double a);
- #ifdef __cplusplus
- }
- #endif
- #endif /*__GENANN_H__*/
|