static void Main()
{
Console.WriteLine("********************************************");
Console.WriteLine("Neural Networks - Project No.2 - BAM network");
Console.WriteLine("********************************************");
#region Prepare the data
// initialize output vectors - phone numbers
var phoneNumbers = new[] { "3120440569", "9114567896", "0538795012", "1234567890", "0508656789" };
// initializing input vectors - 16 bit icons
var db = ReadIcons(phoneNumbers);
Console.WriteLine("\nAssociations Icons: \n");
foreach (var icon in db)
Console.WriteLine(icon.ToString(1));
#endregion
// initialize the BAM neural network wrapper
var bamNeuralNetworkWrapper = new BamNetworkPhoneToIconsWrapper(db,
new PhoneNumberToBiPolarConvertorHuffmanCode(new BinaryToBiPolarVecConvertor()),
new BinaryToBiPolarVecConvertor());
Console.WriteLine("Test BAM Network : \n");
TestInputIconsWithErrorPerentage(db, bamNeuralNetworkWrapper, 0 ,1);
TestInputIconsWithErrorPerentage(db, bamNeuralNetworkWrapper, 20, 5);
TestInputIconsWithErrorPerentage(db, bamNeuralNetworkWrapper, 50, 5);
}
private static void TestInputIconsWithErrorPerentage(IEnumerable<IconInputDataStructure> db,
BamNetworkPhoneToIconsWrapper bamNeuralNetworkWrapper, int errorPercentage, int numberOfTests)
{
Console.WriteLine("Test the input icons with " + errorPercentage + "% random Error");
// check all the input icons
foreach (var iconInputDataStructure in db)
{
Console.ReadKey();
Console.WriteLine("\tInputIcon: ");
Console.WriteLine(iconInputDataStructure.ToString(2));
// create random error icons and test the result
for (var i = 0; i < numberOfTests; i++)
{
Console.ReadKey();
Console.WriteLine("\t\t" + errorPercentage + "% random error icon:");
var errorIcon = iconInputDataStructure.CreateError(errorPercentage);
Console.WriteLine(errorIcon.ToString(3));
// output results
Console.WriteLine("\t\tOutputIcon:");
Console.WriteLine(bamNeuralNetworkWrapper.Associate(errorIcon).ToString(3));
}
}
}
