C#

string data = Convert.ToString(serialPort1.Read(buffer, 0, (int)buffer.Length));<br />
//read using a Stream<br />
string data1 = Convert.ToString(serialPort1.BaseStream.Read(buffer, 0, (int)buffer.Length));<br />

private void button1_Click(object sender, EventArgs e)
        {
            try
            {

                //configuring the serial port
                serialPort1.PortName = "COM6";
                serialPort1.Handshake = Handshake.None;
                serialPort1.BaudRate = 115200;
                serialPort1.DataBits = 8;
                serialPort1.Parity = Parity.None;
                serialPort1.StopBits = StopBits.One;
                serialPort1.DtrEnable = true;

                serialPort1.Open();
                
                string c = "AT+CMGS=";
                string c1 = "\"+6582083412\"\r\n";
                serialPort1.Write(c+c1);


                string d = "Test message from coded program ";
                //Now send the contents of the message
                serialPort1.Write(d);
                //SerialPortListen();
                char[] arr = new char[1];

                arr[0] = (char)26; //ascii value of Ctrl-Z

                serialPort1.Write(arr, 0, 1);
                
                //string data = Convert.ToString(serialPort1.Read(buffer, 0, (int)buffer.Length));
                //read using a Stream
                //string data1 = Convert.ToString(serialPort1.BaseStream.Read(buffer, 0, (int)buffer.Length));
               //MessageBox.Show(data + " part 2 is : " + data1);

                serialPort1.Close();

            }
            catch (Exception ex)
            {
                MessageBox.Show(ex.Message);
            }


        }

        public List<clstypedatapoint> CalcSigmoidSignal(List<clstypedatapoint> sampleData, List<clstypedatapoint> requestPoints)
        {
            updateLogDelegate("Initializing samples");
            updateProgressMDelegate(10);
            List<clstypedatapoint> calcData = new List<clstypedatapoint>();
            foreach (ClsTypeDataPoint p in sampleData)
            {
                ClsTypeDataPoint pt = p;
                pt.Signal = (p.Signal - 128) / 256;
                calcData.Add(pt);
            }



            updateLogDelegate("Initializing neural network.");
            updateProgressMDelegate(20);

            LinearLayer inputLayer = new LinearLayer(2);
            SigmoidLayer hiddenLayer1 = new SigmoidLayer(this.neuronCount);
            SigmoidLayer hiddenLayer2 = new SigmoidLayer(this.neuronCount);
            SigmoidLayer outputLayer = new SigmoidLayer(1);

            BackpropagationConnector bp1 =  new BackpropagationConnector(inputLayer, hiddenLayer1);
            BackpropagationConnector bp3 = new BackpropagationConnector(hiddenLayer1, hiddenLayer2);
            BackpropagationConnector bp2 = new BackpropagationConnector(hiddenLayer2, outputLayer);
            bp1.Momentum = momentum;
            bp2.Momentum = momentum;

            BackpropagationNetwork network = new BackpropagationNetwork(inputLayer, outputLayer);
            
            network.SetLearningRate(learningRate);
            outputLayer.Initializer = new ZeroFunction();
            hiddenLayer1.Initializer = new RandomFunction();
            network.Initialize();

            int progress = 0;
            network.EndEpochEvent += new TrainingEpochEventHandler(delegate(object senderNetwork, TrainingEpochEventArgs args)
            {
                progress++;
                if (progress % 1 == 0)
                {
                    updateProgressTDelegate(((int)((progress) * 100) / trainingCycles)%100);
                    updateLogDelegate("SquaredError: " + network.MeanSquaredError);
                }
            });

            updateLogDelegate("Adding training data.");
            updateProgressMDelegate(30);

            TrainingSet trainingSet = new TrainingSet(2, 1);
            foreach (ClsTypeDataPoint p in calcData)
            {
                trainingSet.Add(new TrainingSample(new double[] { p.Longitude, p.Latitude }, new double[] { (p.Signal)}));
            }

            updateLogDelegate("Training network.");
            updateProgressMDelegate(50);

            network.Learn(trainingSet, trainingCycles);

            network.StopLearning();

            updateProgressTDelegate(0);
            updateLogDelegate("Calculating field.");
            updateProgressMDelegate(90);

            int reqCnt = requestPoints.Count;
            int cnt = 0;
            foreach (ClsTypeDataPoint p in requestPoints)
            {
                cnt++;
                if ((cnt % 100) == 0)
                    updateProgressTDelegate((int)(100 * (cnt) / reqCnt));
                double[] ret; // = new double[];
                ret = network.Run(new double[] { p.Longitude, p.Latitude });
                p.Signal = ret[0];
            }
            updateProgressTDelegate(0);
            updateProgressMDelegate(0);
            return requestPoints;

        }

</clstypedatapoint></clstypedatapoint></clstypedatapoint></clstypedatapoint></clstypedatapoint>