//Generates the response training data
public static void GenerateTrainingData(PhysicallyUncloneableFunction aPUF, double[][] trainingData, double[][] trainingResponse, Random randomGenerator)
{
int trainingSize = trainingData.Length;
int bitNum = aPUF.BitNumber;
for (int i = 0; i < trainingSize; i++)
{
trainingData[i] = GenerateRandomPhiVector(bitNum, randomGenerator);
trainingResponse[i] = new double[1];
trainingResponse[i][0] = aPUF.ComputeResponse(trainingData[i]);
}
}
//Generates the reliability training data as done in Becker's paper, does m/2 - sum(r) calculation
public static void GenerateReliabilityTrainingData(PhysicallyUncloneableFunction aPUF, int numberOfMeasurements, double[][] trainingData, double[][] trainingReliability, Random randomGenerator)
{
int trainingSize = trainingData.Length;
int bitNum = aPUF.BitNumber;
for (int i = 0; i < trainingSize; i++)
{
double sumOfResponses = 0;
//trainingData[i] = GenerateRandomPhiVector(bitNum);
trainingData[i] = GenerateRandomPhiVector(bitNum, randomGenerator);
for (int m = 0; m < numberOfMeasurements; m++)
{
sumOfResponses = sumOfResponses + aPUF.ComputeNoisyResponse(trainingData[i]); //sum the measurements
}
trainingReliability[i] = new double[1];
//trainingReliability[i][0] = sumOfResponses / (double)numberOfMeasurements;
//trainingReliability[i][0] = Math.Abs(numberOfMeasurements / 2.0 - (sumOfResponses / (double)numberOfMeasurements));
trainingReliability[i][0] = Math.Abs(numberOfMeasurements / 2.0 - sumOfResponses);
}
}
