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Posted

Neural Networks on C#

, 19 Nov 2006 GPL3
The articles describes a C# library for neural network computations, and their application for several problem solving.
neuro_demo
Back Propagation
Approximation
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Approximation.exe
Data Samples
sample1.csv
sample2.csv
TimeSeries
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
TimeSeries.exe
XORProblem
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
XORProblem.exe
Simple
Delta Rule Learning
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
2DOrganizing.exe
AForge.dll
AForge.Neuro.dll
Color
AForge.dll
AForge.Neuro.dll
Color.exe
TSP
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
TSP.exe
neuro_src
Docs
AForge.Core.chm
AForge.Neuro.chm
Release
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Samples
Neuro
Back Propagation
Approximation
App.ico
Data Samples
sample1.csv
sample2.csv
TimeSeries
App.ico
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
XORProblem
App.ico
Simple
Delta Rule Learning
App.ico
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
App.ico
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
App.ico
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
App.ico
Color
App.ico
TSP
App.ico
Sources
Controls
Core
Neuro
Activation Functions
Images
sigmoid.bmp
sigmoid_bipolar.bmp
threshold.bmp
Layers
Learning
Networks
Neurons
// AForge Framework
// Approximation using Mutli-Layer Neural Network
//
// Copyright � Andrew Kirillov, 2006
// andrew.kirillov@gmail.com
//

using System;
using System.Drawing;
using System.Collections;
using System.ComponentModel;
using System.Windows.Forms;
using System.Data;

using System.IO;
using System.Threading;

using AForge;
using AForge.Neuro;
using AForge.Neuro.Learning;
using AForge.Controls;

namespace Approximation
{
	/// <summary>
	/// Summary description for Form1.
	/// </summary>
	public class MainForm : System.Windows.Forms.Form
	{
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.ListView dataList;
		private System.Windows.Forms.Button loadDataButton;
		private System.Windows.Forms.ColumnHeader xColumnHeader;
		private System.Windows.Forms.ColumnHeader yColumnHeader;
		private System.Windows.Forms.OpenFileDialog openFileDialog;
		private System.Windows.Forms.GroupBox groupBox2;
		private AForge.Controls.Chart chart;
		private System.Windows.Forms.GroupBox groupBox3;
		private System.Windows.Forms.TextBox momentumBox;
		private System.Windows.Forms.Label label6;
		private System.Windows.Forms.TextBox alphaBox;
		private System.Windows.Forms.Label label2;
		private System.Windows.Forms.TextBox learningRateBox;
		private System.Windows.Forms.Label label1;
		private System.Windows.Forms.Label label8;
		private System.Windows.Forms.TextBox iterationsBox;
		private System.Windows.Forms.Label label10;
		private System.Windows.Forms.Label label9;
		private System.Windows.Forms.GroupBox groupBox4;
		private System.Windows.Forms.TextBox currentErrorBox;
		private System.Windows.Forms.Label label3;
		private System.Windows.Forms.TextBox currentIterationBox;
		private System.Windows.Forms.Label label5;
		private System.Windows.Forms.Button stopButton;
		private System.Windows.Forms.Button startButton;
		private System.Windows.Forms.Label label4;
		private System.Windows.Forms.TextBox neuronsBox;
		/// <summary>
		/// Required designer variable.
		/// </summary>
		private System.ComponentModel.Container components = null;

		private double[,] data = null;

		private double	learningRate = 0.1;
		private double	momentum = 0.0;
		private double	sigmoidAlphaValue = 2.0;
		private int		neuronsInFirstLayer = 20;
		private int		iterations = 1000;

		private Thread	workerThread = null;
		private bool	needToStop = false;

		// Constructor
		public MainForm( )
		{
			//
			// Required for Windows Form Designer support
			//
			InitializeComponent();

			// init chart control
			chart.AddDataSeries( "data", Color.Red, Chart.SeriesType.Dots, 5 );
			chart.AddDataSeries( "solution", Color.Blue, Chart.SeriesType.Line, 1 );

			// init controls
			UpdateSettings( );
		}

		/// <summary>
		/// Clean up any resources being used.
		/// </summary>
		protected override void Dispose( bool disposing )
		{
			if( disposing )
			{
				if (components != null) 
				{
					components.Dispose();
				}
			}
			base.Dispose( disposing );
		}

		#region Windows Form Designer generated code
		/// <summary>
		/// Required method for Designer support - do not modify
		/// the contents of this method with the code editor.
		/// </summary>
		private void InitializeComponent()
		{
			this.groupBox1 = new System.Windows.Forms.GroupBox();
			this.dataList = new System.Windows.Forms.ListView();
			this.loadDataButton = new System.Windows.Forms.Button();
			this.xColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.yColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.openFileDialog = new System.Windows.Forms.OpenFileDialog();
			this.groupBox2 = new System.Windows.Forms.GroupBox();
			this.chart = new AForge.Controls.Chart();
			this.groupBox3 = new System.Windows.Forms.GroupBox();
			this.momentumBox = new System.Windows.Forms.TextBox();
			this.label6 = new System.Windows.Forms.Label();
			this.alphaBox = new System.Windows.Forms.TextBox();
			this.label2 = new System.Windows.Forms.Label();
			this.learningRateBox = new System.Windows.Forms.TextBox();
			this.label1 = new System.Windows.Forms.Label();
			this.label8 = new System.Windows.Forms.Label();
			this.iterationsBox = new System.Windows.Forms.TextBox();
			this.label10 = new System.Windows.Forms.Label();
			this.label9 = new System.Windows.Forms.Label();
			this.groupBox4 = new System.Windows.Forms.GroupBox();
			this.currentErrorBox = new System.Windows.Forms.TextBox();
			this.label3 = new System.Windows.Forms.Label();
			this.currentIterationBox = new System.Windows.Forms.TextBox();
			this.label5 = new System.Windows.Forms.Label();
			this.stopButton = new System.Windows.Forms.Button();
			this.startButton = new System.Windows.Forms.Button();
			this.label4 = new System.Windows.Forms.Label();
			this.neuronsBox = new System.Windows.Forms.TextBox();
			this.groupBox1.SuspendLayout();
			this.groupBox2.SuspendLayout();
			this.groupBox3.SuspendLayout();
			this.groupBox4.SuspendLayout();
			this.SuspendLayout();
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.Add(this.dataList);
			this.groupBox1.Controls.Add(this.loadDataButton);
			this.groupBox1.Location = new System.Drawing.Point(10, 10);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(180, 320);
			this.groupBox1.TabIndex = 1;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Data";
			// 
			// dataList
			// 
			this.dataList.Columns.AddRange(new System.Windows.Forms.ColumnHeader[] {
																					   this.xColumnHeader,
																					   this.yColumnHeader});
			this.dataList.FullRowSelect = true;
			this.dataList.GridLines = true;
			this.dataList.Location = new System.Drawing.Point(10, 20);
			this.dataList.Name = "dataList";
			this.dataList.Size = new System.Drawing.Size(160, 255);
			this.dataList.TabIndex = 0;
			this.dataList.View = System.Windows.Forms.View.Details;
			// 
			// loadDataButton
			// 
			this.loadDataButton.Location = new System.Drawing.Point(10, 285);
			this.loadDataButton.Name = "loadDataButton";
			this.loadDataButton.TabIndex = 1;
			this.loadDataButton.Text = "&Load";
			this.loadDataButton.Click += new System.EventHandler(this.loadDataButton_Click);
			// 
			// xColumnHeader
			// 
			this.xColumnHeader.Text = "X";
			// 
			// yColumnHeader
			// 
			this.yColumnHeader.Text = "Y";
			// 
			// openFileDialog
			// 
			this.openFileDialog.Filter = "CSV (Comma delimited) (*.csv)|*.csv";
			this.openFileDialog.Title = "Select data file";
			// 
			// groupBox2
			// 
			this.groupBox2.Controls.Add(this.chart);
			this.groupBox2.Location = new System.Drawing.Point(200, 10);
			this.groupBox2.Name = "groupBox2";
			this.groupBox2.Size = new System.Drawing.Size(300, 320);
			this.groupBox2.TabIndex = 2;
			this.groupBox2.TabStop = false;
			this.groupBox2.Text = "Function";
			// 
			// chart
			// 
			this.chart.Location = new System.Drawing.Point(10, 20);
			this.chart.Name = "chart";
			this.chart.Size = new System.Drawing.Size(280, 290);
			this.chart.TabIndex = 0;
			// 
			// groupBox3
			// 
			this.groupBox3.Controls.Add(this.neuronsBox);
			this.groupBox3.Controls.Add(this.label4);
			this.groupBox3.Controls.Add(this.momentumBox);
			this.groupBox3.Controls.Add(this.label6);
			this.groupBox3.Controls.Add(this.alphaBox);
			this.groupBox3.Controls.Add(this.label2);
			this.groupBox3.Controls.Add(this.learningRateBox);
			this.groupBox3.Controls.Add(this.label1);
			this.groupBox3.Controls.Add(this.label8);
			this.groupBox3.Controls.Add(this.iterationsBox);
			this.groupBox3.Controls.Add(this.label10);
			this.groupBox3.Controls.Add(this.label9);
			this.groupBox3.Location = new System.Drawing.Point(510, 10);
			this.groupBox3.Name = "groupBox3";
			this.groupBox3.Size = new System.Drawing.Size(195, 195);
			this.groupBox3.TabIndex = 4;
			this.groupBox3.TabStop = false;
			this.groupBox3.Text = "Settings";
			// 
			// momentumBox
			// 
			this.momentumBox.Location = new System.Drawing.Point(125, 45);
			this.momentumBox.Name = "momentumBox";
			this.momentumBox.Size = new System.Drawing.Size(60, 20);
			this.momentumBox.TabIndex = 3;
			this.momentumBox.Text = "";
			// 
			// label6
			// 
			this.label6.Location = new System.Drawing.Point(10, 47);
			this.label6.Name = "label6";
			this.label6.Size = new System.Drawing.Size(82, 17);
			this.label6.TabIndex = 2;
			this.label6.Text = "Momentum:";
			// 
			// alphaBox
			// 
			this.alphaBox.Location = new System.Drawing.Point(125, 70);
			this.alphaBox.Name = "alphaBox";
			this.alphaBox.Size = new System.Drawing.Size(60, 20);
			this.alphaBox.TabIndex = 5;
			this.alphaBox.Text = "";
			// 
			// label2
			// 
			this.label2.Location = new System.Drawing.Point(10, 72);
			this.label2.Name = "label2";
			this.label2.Size = new System.Drawing.Size(120, 15);
			this.label2.TabIndex = 4;
			this.label2.Text = "Sigmoid\'s alpha value:";
			// 
			// learningRateBox
			// 
			this.learningRateBox.Location = new System.Drawing.Point(125, 20);
			this.learningRateBox.Name = "learningRateBox";
			this.learningRateBox.Size = new System.Drawing.Size(60, 20);
			this.learningRateBox.TabIndex = 1;
			this.learningRateBox.Text = "";
			// 
			// label1
			// 
			this.label1.Location = new System.Drawing.Point(10, 22);
			this.label1.Name = "label1";
			this.label1.Size = new System.Drawing.Size(78, 14);
			this.label1.TabIndex = 0;
			this.label1.Text = "Learning rate:";
			// 
			// label8
			// 
			this.label8.BorderStyle = System.Windows.Forms.BorderStyle.Fixed3D;
			this.label8.Location = new System.Drawing.Point(10, 147);
			this.label8.Name = "label8";
			this.label8.Size = new System.Drawing.Size(175, 2);
			this.label8.TabIndex = 22;
			// 
			// iterationsBox
			// 
			this.iterationsBox.Location = new System.Drawing.Point(125, 155);
			this.iterationsBox.Name = "iterationsBox";
			this.iterationsBox.Size = new System.Drawing.Size(60, 20);
			this.iterationsBox.TabIndex = 9;
			this.iterationsBox.Text = "";
			// 
			// label10
			// 
			this.label10.Font = new System.Drawing.Font("Microsoft Sans Serif", 6.75F, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, ((System.Byte)(0)));
			this.label10.Location = new System.Drawing.Point(126, 175);
			this.label10.Name = "label10";
			this.label10.Size = new System.Drawing.Size(58, 14);
			this.label10.TabIndex = 25;
			this.label10.Text = "( 0 - inifinity )";
			// 
			// label9
			// 
			this.label9.Location = new System.Drawing.Point(10, 157);
			this.label9.Name = "label9";
			this.label9.Size = new System.Drawing.Size(70, 16);
			this.label9.TabIndex = 8;
			this.label9.Text = "Iterations:";
			// 
			// groupBox4
			// 
			this.groupBox4.Controls.Add(this.currentErrorBox);
			this.groupBox4.Controls.Add(this.label3);
			this.groupBox4.Controls.Add(this.currentIterationBox);
			this.groupBox4.Controls.Add(this.label5);
			this.groupBox4.Location = new System.Drawing.Point(510, 210);
			this.groupBox4.Name = "groupBox4";
			this.groupBox4.Size = new System.Drawing.Size(195, 75);
			this.groupBox4.TabIndex = 6;
			this.groupBox4.TabStop = false;
			this.groupBox4.Text = "Current iteration";
			// 
			// currentErrorBox
			// 
			this.currentErrorBox.Location = new System.Drawing.Point(125, 45);
			this.currentErrorBox.Name = "currentErrorBox";
			this.currentErrorBox.ReadOnly = true;
			this.currentErrorBox.Size = new System.Drawing.Size(60, 20);
			this.currentErrorBox.TabIndex = 3;
			this.currentErrorBox.Text = "";
			// 
			// label3
			// 
			this.label3.Location = new System.Drawing.Point(10, 47);
			this.label3.Name = "label3";
			this.label3.Size = new System.Drawing.Size(70, 16);
			this.label3.TabIndex = 2;
			this.label3.Text = "Error:";
			// 
			// currentIterationBox
			// 
			this.currentIterationBox.Location = new System.Drawing.Point(125, 20);
			this.currentIterationBox.Name = "currentIterationBox";
			this.currentIterationBox.ReadOnly = true;
			this.currentIterationBox.Size = new System.Drawing.Size(60, 20);
			this.currentIterationBox.TabIndex = 1;
			this.currentIterationBox.Text = "";
			// 
			// label5
			// 
			this.label5.Location = new System.Drawing.Point(10, 22);
			this.label5.Name = "label5";
			this.label5.Size = new System.Drawing.Size(70, 16);
			this.label5.TabIndex = 0;
			this.label5.Text = "Iteration:";
			// 
			// stopButton
			// 
			this.stopButton.Enabled = false;
			this.stopButton.Location = new System.Drawing.Point(630, 305);
			this.stopButton.Name = "stopButton";
			this.stopButton.TabIndex = 8;
			this.stopButton.Text = "S&top";
			this.stopButton.Click += new System.EventHandler(this.stopButton_Click);
			// 
			// startButton
			// 
			this.startButton.Enabled = false;
			this.startButton.Location = new System.Drawing.Point(540, 305);
			this.startButton.Name = "startButton";
			this.startButton.TabIndex = 7;
			this.startButton.Text = "&Start";
			this.startButton.Click += new System.EventHandler(this.startButton_Click);
			// 
			// label4
			// 
			this.label4.Location = new System.Drawing.Point(10, 97);
			this.label4.Name = "label4";
			this.label4.Size = new System.Drawing.Size(115, 15);
			this.label4.TabIndex = 6;
			this.label4.Text = "Neurons in first layer:";
			// 
			// neuronsBox
			// 
			this.neuronsBox.Location = new System.Drawing.Point(125, 95);
			this.neuronsBox.Name = "neuronsBox";
			this.neuronsBox.Size = new System.Drawing.Size(60, 20);
			this.neuronsBox.TabIndex = 7;
			this.neuronsBox.Text = "";
			// 
			// MainForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(714, 338);
			this.Controls.Add(this.stopButton);
			this.Controls.Add(this.startButton);
			this.Controls.Add(this.groupBox4);
			this.Controls.Add(this.groupBox3);
			this.Controls.Add(this.groupBox2);
			this.Controls.Add(this.groupBox1);
			this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedDialog;
			this.MaximizeBox = false;
			this.Name = "MainForm";
			this.Text = "Approximation using Multi-Layer Neural Network";
			this.Closing += new System.ComponentModel.CancelEventHandler(this.MainForm_Closing);
			this.groupBox1.ResumeLayout(false);
			this.groupBox2.ResumeLayout(false);
			this.groupBox3.ResumeLayout(false);
			this.groupBox4.ResumeLayout(false);
			this.ResumeLayout(false);

		}
		#endregion

		/// <summary>
		/// The main entry point for the application.
		/// </summary>
		[STAThread]
		static void Main( ) 
		{
			Application.Run( new MainForm( ) );
		}

		// On main form closing
		private void MainForm_Closing(object sender, System.ComponentModel.CancelEventArgs e)
		{
			// check if worker thread is running
			if ( ( workerThread != null ) && ( workerThread.IsAlive ) )
			{
				needToStop = true;
				workerThread.Join( );
			}
		}

		// Update settings controls
		private void UpdateSettings( )
		{
			learningRateBox.Text	= learningRate.ToString( );
			momentumBox.Text		= momentum.ToString( );
			alphaBox.Text			= sigmoidAlphaValue.ToString( );
			neuronsBox.Text			= neuronsInFirstLayer.ToString( );
			iterationsBox.Text		= iterations.ToString( );
		}
		
		// Load data
		private void loadDataButton_Click(object sender, System.EventArgs e)
		{
			// show file selection dialog
			if ( openFileDialog.ShowDialog( ) == DialogResult.OK )
			{
				StreamReader reader = null;
				// read maximum 50 points
				double[,] tempData = new double[50, 2];
				double minX = double.MaxValue;
				double maxX = double.MinValue;

				try
				{
					// open selected file
					reader = File.OpenText( openFileDialog.FileName );
					string	str = null;
					int		i = 0;

					// read the data
					while ( ( i < 50 ) && ( ( str = reader.ReadLine( ) ) != null ) )
					{
						string[] strs = str.Split( ';' );
						if ( strs.Length == 1 )
							strs = str.Split( ',' );
						// parse X
						tempData[i, 0] = double.Parse( strs[0] );
						tempData[i, 1] = double.Parse( strs[1] );

						// search for min value
						if ( tempData[i, 0] < minX )
							minX = tempData[i, 0];
						// search for max value
						if ( tempData[i, 0] > maxX )
							maxX = tempData[i, 0];

						i++;
					}

					// allocate and set data
					data = new double[i, 2];
					Array.Copy( tempData, 0, data, 0, i * 2 );
				}
				catch (Exception)
				{
					MessageBox.Show( "Failed reading the file", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error );
					return;
				}
				finally
				{
					// close file
					if ( reader != null )
						reader.Close( );
				}

				// update list and chart
				UpdateDataListView( );
				chart.RangeX = new DoubleRange( minX, maxX );
				chart.UpdateDataSeries( "data", data );
				chart.UpdateDataSeries( "solution", null );
				// enable "Start" button
				startButton.Enabled = true;
			}
		}

		// Update data in list view
		private void UpdateDataListView( )
		{
			// remove all current records
			dataList.Items.Clear( );
			// add new records
			for ( int i = 0, n = data.GetLength( 0 ); i < n; i++ )
			{
				dataList.Items.Add( data[i, 0].ToString( ) );
				dataList.Items[i].SubItems.Add( data[i, 1].ToString( ) );
			}
		}

		// Enable/disale controls
		private void EnableControls( bool enable )
		{
			loadDataButton.Enabled		= enable;
			learningRateBox.Enabled		= enable;
			momentumBox.Enabled			= enable;
			alphaBox.Enabled			= enable;
			neuronsBox.Enabled			= enable;
			iterationsBox.Enabled		= enable;

			startButton.Enabled	= enable;
			stopButton.Enabled	= !enable;
		}

		// On button "Start"
		private void startButton_Click( object sender, System.EventArgs e )
		{
			// get learning rate
			try
			{
				learningRate = Math.Max( 0.00001, Math.Min( 1, double.Parse( learningRateBox.Text ) ) );
			}
			catch
			{
				learningRate = 0.1;
			}
			// get momentum
			try
			{
				momentum = Math.Max( 0, Math.Min( 0.5, double.Parse( momentumBox.Text ) ) );
			}
			catch
			{
				momentum = 0;
			}
			// get sigmoid's alpha value
			try
			{
				sigmoidAlphaValue = Math.Max( 0.001, Math.Min( 50, double.Parse( alphaBox.Text ) ) );
			}
			catch
			{
				sigmoidAlphaValue = 2;
			}
			// get neurons count in first layer
			try
			{
				neuronsInFirstLayer = Math.Max( 5, Math.Min( 50, int.Parse( neuronsBox.Text ) ) );
			}
			catch
			{
				neuronsInFirstLayer = 20;
			}
			// iterations
			try
			{
				iterations = Math.Max( 0, int.Parse( iterationsBox.Text ) );
			}
			catch
			{
				iterations = 1000;
			}
			// update settings controls
			UpdateSettings( );
		
			// disable all settings controls except "Stop" button
			EnableControls( false );

			// run worker thread
			needToStop = false;
			workerThread = new Thread( new ThreadStart( SearchSolution ) );
			workerThread.Start( );
		}

		// On button "Stop"
		private void stopButton_Click( object sender, System.EventArgs e )
		{
			// stop worker thread
			needToStop = true;
			workerThread.Join( );
			workerThread = null;
		}

		// Worker thread
		void SearchSolution( )
		{
			// number of learning samples
			int samples = data.GetLength( 0 );
			// data transformation factor
			double yFactor = 1.7 / chart.RangeY.Length;
			double yMin = chart.RangeY.Min;
			double xFactor = 2.0 / chart.RangeX.Length;
			double xMin = chart.RangeX.Min;

			// prepare learning data
			double[][] input = new double[samples][];
			double[][] output = new double[samples][];

			for ( int i = 0; i < samples; i++ )
			{
				input[i] = new double[1];
				output[i] = new double[1];

				// set input
				input[i][0] = ( data[i, 0] - xMin ) * xFactor - 1.0;
				// set output
				output[i][0] = ( data[i, 1] - yMin ) * yFactor - 0.85;
			}

			// create multi-layer neural network
			ActivationNetwork	network = new ActivationNetwork(
				new BipolarSigmoidFunction( sigmoidAlphaValue ),
				1, neuronsInFirstLayer, 1 );
			// create teacher
			BackPropagationLearning teacher = new BackPropagationLearning( network );
			// set learning rate and momentum
			teacher.LearningRate	= learningRate;
			teacher.Momentum		= momentum;

			// iterations
			int iteration = 1;

			// solution array
			double[,]	solution = new double[50, 2];
			double[]	networkInput = new double[1];

			// calculate X values to be used with solution function
			for ( int j = 0; j < 50; j++ )
			{
				solution[j, 0] = chart.RangeX.Min + (double) j * chart.RangeX.Length / 49;
			}

			// loop
			while ( !needToStop )
			{
				// run epoch of learning procedure
				double error = teacher.RunEpoch( input, output ) / samples;

				// calculate solution
				for ( int j = 0; j < 50; j++ )
				{
					networkInput[0] = ( solution[j, 0] - xMin ) * xFactor - 1.0;
					solution[j, 1] = ( network.Compute( networkInput )[0] + 0.85 ) / yFactor + yMin;
				}
				chart.UpdateDataSeries( "solution", solution );
				// calculate error
				double learningError = 0.0;
				for ( int j = 0, k = data.GetLength( 0 ); j < k; j++ )
				{
					networkInput[0] = input[j][0];
					learningError += Math.Abs( data[j, 1] - ( ( network.Compute( networkInput )[0] + 0.85 ) / yFactor + yMin ) );
				}
			
				// set current iteration's info
				currentIterationBox.Text = iteration.ToString( );
				currentErrorBox.Text = learningError.ToString( "F3" );

				// increase current iteration
				iteration++;

				// check if we need to stop
				if ( ( iterations != 0 ) && ( iteration > iterations ) )
					break;
			}


			// enable settings controls
			EnableControls( true );
		}
	}
}

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About the Author

Andrew Kirillov
Software Developer IBM
United Kingdom United Kingdom
Started software development at about 15 years old and it seems like now it lasts most part of my life. Fortunately did not spend too much time with Z80 and BK0010 and switched to 8086 and further. Similar with programming languages – luckily managed to get away from BASIC and Pascal to things like Assembler, C, C++ and then C#. Apart from daily programming for food, do it also for hobby, where mostly enjoy areas like Computer Vision, Robotics and AI. This led to some open source stuff like AForge.NET and not so open Computer Vision Sandbox.

Going out of computers I am just a man loving his family, enjoying traveling, a bit of books, a bit of movies and a mixture of everything else. Always wanted to learn playing guitar, but it seems like 6 strings are much harder than few dozens of keyboard’s keys. Will keep progressing ...

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