1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
// Simple nn that can learn XOR
double sigmoid(double x) {return 1 / (1 + exp(-x)); }
double dSigmoid(double x) {return x * (1-x); }
double init_weights(){return ((double)rand()) / ((double)RAND_MAX); }
void shuffle(int *array, size_t n){
if (n > 1){
size_t i;
for (i = 0; i < n -1; i++){
size_t j = i + rand() / (RAND_MAX / (n - i) + 1);
int t = array[j];
array[j] = array[i];
array[i] = t;
}
}
}
#define numInputs 2
#define numHiddenNodes 2
#define numOutputs 1
#define numTrainingSets 4
int main(void){
const double lr = 0.1f;
double hiddenLayer[numHiddenNodes];
double outputLayer[numOutputs];
double hiddenLayerBias[numHiddenNodes];
double outputLayerBias[numOutputs];
double hiddenWeights[numInputs][numHiddenNodes];
double outputWeights[numHiddenNodes][numOutputs];
double training_inputs[numTrainingSets][numInputs] = {{0.0f,0.0f},{1.0f,0.0f},{0.0f,1.0f},{1.0f},{1.0f}};
double training_outputs[numTrainingSets][numOutputs] = {{0.0f},{1.0f},{1.0f},{0.0f}};
}
|