📄 backprop.h
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/*
******************************************************************
* HISTORY
* 15-Oct-94 Jeff Shufelt (js), Carnegie Mellon University
* Prepared for 15-681, Fall 1994.
*
******************************************************************
*/
#ifndef _BACKPROP_H_
#define _BACKPROP_H_
#define BIGRND 0x7fffffff
/*** The neural network data structure. The network is assumed to
be a fully-connected feedforward three-layer network.
Unit 0 in each layer of units is the threshold unit; this means
that the remaining units are indexed from 1 to n, inclusive.
***/
typedef struct {
int input_n; /* number of input units */
int hidden_n; /* number of hidden units */
int output_n; /* number of output units */
double *input_units; /* the input units */
double *hidden_units; /* the hidden units */
double *output_units; /* the output units */
double *hidden_delta; /* storage for hidden unit error */
double *output_delta; /* storage for output unit error */
double *target; /* storage for target vector */
double **input_weights; /* weights from input to hidden layer */
double **hidden_weights; /* weights from hidden to output layer */
/*** The next two are for momentum ***/
double **input_prev_weights; /* previous change on input to hidden wgt */
double **hidden_prev_weights; /* previous change on hidden to output wgt */
} BPNN;
/*** User-level functions ***/
void bpnn_initialize();
BPNN *bpnn_create();
void bpnn_free();
void bpnn_train();
void bpnn_feedforward();
void bpnn_save();
BPNN *bpnn_read();
#endif
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