ls

Xenith/core.h

@@ -1,9 +1,28 @@
+#ifndef CORE_H
+#define CORE_H
 
-class NeuroEngine: {
-    private:
-        void* m_engine;
-    public:
-        NeuroEngine();
-        ~NeuroEngine();
-        void* getEngine();
-}
+#include "typedef.h"
+#include <vector>
+#include <cmath>
+#include <iostream>
+#include <cstdlib>
+
+class NeuralNetwork {
+private:
+    int numLayers;
+    std::vector<int> layerSizes;
+    std::vector<std::vector<std::vector<double>>> weights; // weights[layer][to_node][from_node]
+    std::vector<std::vector<double>> biases;             // biases[layer][node]
+    std::vector<std::vector<double>> outputs;            // Храним выходы слоев для backprop
+
+    double sigmoid(double x) { return 1.0 / (1.0 + exp(-x)); }
+    double sigmoidDerivative(double x) { return x * (1.0 - x); }
+
+public:
+    NeuralNetwork(LayerStructure_t layers[], int count);
+    
+    std::vector<double> feedForward(std::vector<double> input);
+    void train(std::vector<double> input, std::vector<double> target, double learningRate);
+};
+
+#endif