yeah

src/NeuralNetwork/FeedForward.cpp

@@ -33,7 +33,7 @@ FFNeuron& FFLayer::operator[](const size_t& neuron)
 
 }
 
-FeedForward::FeedForward(std::initializer_list<size_t> s, double lam): ACyclicNetwork(lam),layers(s.size())
+FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, std::function<float(const size_t&layer, const size_t &neuron, const size_t &weight)> weightInit): ACyclicNetwork(lam),layers(s.size())
 {
 	transfer = new TransferFunction::TransferFunction*[s.size()];
 	weights= new float**[s.size()];
@@ -41,7 +41,7 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam): ACyclicNe
 	layerSizes= new size_t[s.size()];
 	outputs= new float*[s.size()];
 	inputs= new float*[s.size()];
-	int i=0;
+	register int i=0;
 	register int prev_size=1;
 	for(int layeSize:s) // TODO rename
 	{
@@ -65,7 +65,7 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam): ACyclicNe
 			weights[i][j]= new float[prev_size];
 			for(int k=0;k<prev_size;k++)
 			{
-				weights[i][j][k]=1.0-((float)(rand()%2001))/1000.0;
+				weights[i][j][k]=weightInit(i,j,k);
 			}
 		}
 		i++;
@@ -173,7 +173,7 @@ Shin::Solution FeedForward::solve(const Shin::Problem& p)
 		{
 			std::vector<std::thread> th;
 			size_t s=1;
-			size_t step =layerSizes[i]/threads;
+			register size_t step =layerSizes[i]/threads;
 			for(size_t t=1;t<threads;t++)
 			{
 				th.push_back(std::thread([i,this,newSolution,prevSize,sol](size_t from, size_t to)->void{

src/NeuralNetwork/FeedForward.h

@@ -81,7 +81,10 @@ namespace NeuralNetwork
 	class FeedForward:public ACyclicNetwork
 	{
 		public:
-			FeedForward(std::initializer_list<size_t> s, double lam=Shin::NeuralNetwork::lambda);
+			FeedForward(std::initializer_list<size_t> s, double lam=Shin::NeuralNetwork::lambda,
+				std::function<float(const size_t&layer, const size_t &neuron, const size_t &weight)> weightInit=
+					[](const size_t&, const size_t &, const size_t &)->float{ return 1.0-((float)(rand()%2001))/1000.0;}
+			);
 			virtual ~FeedForward();
 
 			FeedForward(const FeedForward &f) = delete; //TODO

src/NeuralNetwork/Perceptron.h

@@ -0,0 +1,26 @@
+#ifndef _S_NN_PERCEP_H_
+#define _S_NN_PERCEP_H_
+
+#include "./FeedForward"
+#include "TransferFunction/Heaviside.h"
+
+namespace Shin
+{
+namespace NeuralNetwork
+{
+	class Perceptron:public FeedForward
+	{
+		public:
+			Perceptron(const size_t &inputSize, const size_t &outputSize):FeedForward({inputSize,outputSize})
+			{
+				for(int i=0;i<layers;i++)
+				{
+					delete transfer[i];
+					transfer[i]= new TransferFunction::Heaviside(0.5);
+				}
+			};
+	};
+
+}
+}
+#endif