/* ****************************************************************** * 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