diff options
Diffstat (limited to 'neural.c')
| -rw-r--r-- | neural.c | 75 |
1 files changed, 70 insertions, 5 deletions
@@ -6,11 +6,6 @@ #include "nmglobal.h" #include "nbench1.h" -/* -** The Neural Net test requires an input data file. -** The name is specified here. -*/ -char *inpath="NNET.DAT"; /******************************** ** BACK PROPAGATION NEURAL NET ** @@ -37,6 +32,76 @@ char *inpath="NNET.DAT"; ** on systems other than a Macintosh -- RG */ +/* +** DEFINES +*/ +#define T 1 /* TRUE */ +#define F 0 /* FALSE */ +#define ERR -1 +#define MAXPATS 10 /* max number of patterns in data file */ +#define IN_X_SIZE 5 /* number of neurodes/row of input layer */ +#define IN_Y_SIZE 7 /* number of neurodes/col of input layer */ +#define IN_SIZE 35 /* equals IN_X_SIZE*IN_Y_SIZE */ +#define MID_SIZE 8 /* number of neurodes in middle layer */ +#define OUT_SIZE 8 /* number of neurodes in output layer */ +#define MARGIN 0.1 /* how near to 1,0 do we have to come to stop? */ +#define BETA 0.09 /* beta learning constant */ +#define ALPHA 0.09 /* momentum term constant */ +#define STOP 0.1 /* when worst_error less than STOP, training is done */ + +/* +** The Neural Net test requires an input data file. +** The name is specified here. +*/ +char *inpath="NNET.DAT"; + +/* +** GLOBALS +*/ +double mid_wts[MID_SIZE][IN_SIZE]; /* middle layer weights */ +double out_wts[OUT_SIZE][MID_SIZE]; /* output layer weights */ +double mid_out[MID_SIZE]; /* middle layer output */ +double out_out[OUT_SIZE]; /* output layer output */ +double mid_error[MID_SIZE]; /* middle layer errors */ +double out_error[OUT_SIZE]; /* output layer errors */ +double mid_wt_change[MID_SIZE][IN_SIZE]; /* storage for last wt change */ +double out_wt_change[OUT_SIZE][MID_SIZE]; /* storage for last wt change */ +double in_pats[MAXPATS][IN_SIZE]; /* input patterns */ +double out_pats[MAXPATS][OUT_SIZE]; /* desired output patterns */ +double tot_out_error[MAXPATS]; /* measure of whether net is done */ +double out_wt_cum_change[OUT_SIZE][MID_SIZE]; /* accumulated wt changes */ +double mid_wt_cum_change[MID_SIZE][IN_SIZE]; /* accumulated wt changes */ + +double worst_error; /* worst error each pass through the data */ +double average_error; /* average error each pass through the data */ +double avg_out_error[MAXPATS]; /* average error each pattern */ + +int iteration_count; /* number of passes thru network so far */ +int numpats; /* number of patterns in data file */ +int numpasses; /* number of training passes through data file */ +int learned; /* flag--if TRUE, network has learned all patterns */ + +/* +** PROTOTYPES +*/ +static unsigned long DoNNetIteration(unsigned long nloops); +static void do_mid_forward(int patt); +static void do_out_forward(); +void display_output(int patt); +static void do_forward_pass(int patt); +static void do_out_error(int patt); +static void worst_pass_error(); +static void do_mid_error(); +static void adjust_out_wts(); +static void adjust_mid_wts(); +static void do_back_pass(int patt); +static void move_wt_changes(); +static int check_out_error(); +static void zero_changes(); +static void randomize_wts(); +static int read_data_file(); +/* static int initialize_net(); */ + /*********** ** DoNNet ** ************ |