perceptron implementation changed + perceptronLearningAlgorithm and tests

tests/CMakeLists.txt

@@ -25,6 +25,12 @@ target_link_libraries(feedforward_perf NeuralNetwork)
 add_executable(optical_backpropagation optical_backpropagation.cpp)
 target_link_libraries(optical_backpropagation NeuralNetwork)
 
+add_executable(perceptron perceptron.cpp)
+target_link_libraries(perceptron NeuralNetwork)
+
+add_executable(perceptron_learning perceptron_learning.cpp)
+target_link_libraries(perceptron_learning NeuralNetwork)
+
 add_executable(recurrent recurrent.cpp)
 target_link_libraries(recurrent NeuralNetwork)
 

tests/perceptron.cpp

@@ -0,0 +1,16 @@
+#include <NeuralNetwork/FeedForward/Perceptron.h>
+
+#include <assert.h>
+#include <iostream>
+
+int main() {
+	NeuralNetwork::FeedForward::Perceptron p(2,1);
+
+	p[1].weight(0)=-1.0;
+	p[1].weight(1)=1.001;
+
+	assert(p.computeOutput({1,1})[0] == 1.0);
+	p[1].weight(1)=0.999;
+
+	assert(p.computeOutput({1,1})[0] == 0.0);
+}

tests/perceptron_learning.cpp

@@ -0,0 +1,41 @@
+#include <NeuralNetwork/Learning/PerceptronLearning.h>
+
+#include <cassert>
+#include <iostream>
+
+int main() {
+	{	// XOR problem
+		NeuralNetwork::FeedForward::Perceptron n(2,1);
+
+		n.randomizeWeights();
+
+		NeuralNetwork::Learning::PerceptronLearning learn(n);
+
+		for(int i=0;i<10;i++) {
+			learn.teach({1,0},{1});
+			learn.teach({1,1},{1});
+			learn.teach({0,0},{0});
+			learn.teach({0,1},{1});
+		}
+
+		{
+			std::vector<float> ret =n.computeOutput({1,1});
+			assert(ret[0] > 0.9);
+		}
+
+		{
+			std::vector<float> ret =n.computeOutput({0,1});
+			assert(ret[0] > 0.9);
+		}
+
+		{
+			std::vector<float> ret =n.computeOutput({1,0});
+			assert(ret[0] > 0.9);
+		}
+
+		{
+			std::vector<float> ret =n.computeOutput({0,0});
+			assert(ret[0] < 0.1);
+		}
+	}
+}