Neural Networks on C#

// AForge Neural Net Library
//
// Copyright � Andrew Kirillov, 2005-2006
// andrew.kirillov@gmail.com
//

namespace AForge.Neuro
{
	using System;
	using AForge;

	/// <summary>
	/// Base neuron class
	/// </summary>
	/// 
	/// <remarks>This is a base neuron class, which encapsulates such
	/// common properties, like neuron's input, output and weights.</remarks>
	/// 
	public abstract class Neuron
	{
		/// <summary>
		/// Neuron's inputs count
		/// </summary>
		protected int		inputsCount = 0;

		/// <summary>
		/// Nouron's wieghts
		/// </summary>
		protected double[]	weights = null;

		/// <summary>
		/// Neuron's output value
		/// </summary>
		protected double	output = 0;				

		/// <summary>
		/// Random number generator
		/// </summary>
		/// 
		/// <remarks>The generator is used for neuron's weights randomization</remarks>
		/// 
		protected static Random	rand = new Random( (int) DateTime.Now.Ticks );

		/// <summary>
		/// Random generator range
		/// </summary>
		/// 
		/// <remarks>Sets the range of random generator. Affects initial values of neuron's weight.
		/// Default value is [0, 1].</remarks>
		/// 
		protected static DoubleRange randRange = new DoubleRange( 0.0, 1.0 );

		/// <summary>
		/// Random number generator
		/// </summary>
		/// 
		/// <remarks>The property allows to initialize random generator with a custom seed. The generator is
		/// used for neuron's weights randomization.</remarks>
		/// 
		public static Random RandGenerator
		{
			get { return rand; }
			set
			{
				if ( value != null )
				{
					rand = value;
				}
			}
		}

		/// <summary>
		/// Random generator range
		/// </summary>
		public static DoubleRange RandRange
		{
			get { return randRange; }
			set
			{
				if ( value != null )
				{
					randRange = value;
				}
			}
		}

		/// <summary>
		/// Neuron's inputs count
		/// </summary>
		public int InputsCount
		{
			get { return inputsCount; }
		}

		/// <summary>
		/// Neuron's output value
		/// </summary>
		/// 
		/// <remarks>The calculation way of neuron's output value is determined by inherited class.</remarks>
		/// 
		public double Output
		{
			get { return output; }
		}

		/// <summary>
		/// Neuron's weights accessor
		/// </summary>
		/// 
		/// <param name="index">Weight index</param>
		/// 
		/// <remarks>Allows to access neuron's weights.</remarks>
		/// 
		public double this[int index]
		{
			get { return weights[index]; }
			set { weights[index] = value; }
		}

		/// <summary>
		/// Initializes a new instance of the <see cref="Neuron"/> class
		/// </summary>
		///
		/// <param name="inputs">Neuron's inputs count</param>
		/// 
		/// <remarks>The new neuron will be randomized (see <see cref="Randomize"/> method)
		/// after it is created.</remarks>
		///
		public Neuron( int inputs )
		{
			// allocate weights
			inputsCount = Math.Max( 1, inputs );
			weights = new double[inputsCount];
			// randomize the neuron
			Randomize( );
		}

		/// <summary>
		/// Randomize neuron 
		/// </summary>
		/// 
		/// <remarks>Initialize neuron's weights with random values within the range specified
		/// by <see cref="RandRange"/>.</remarks>
		/// 
		public virtual void Randomize( )
		{
			double d = randRange.Length;

			// randomize weights
			for ( int i = 0; i < inputsCount; i++ )
				weights[i] = rand.NextDouble( ) * d + randRange.Min;
		}

		/// <summary>
		/// Computes output value of neuron
		/// </summary>
		/// 
		/// <param name="input">Input vector</param>
		/// 
		/// <returns>Returns neuron's output value</returns>
		/// 
		/// <remarks>The actual neuron's output value is determined by inherited class.
		/// The output value is also stored in <see cref="Output"/> property.</remarks>
		/// 
		public abstract double Compute( double[] input );
	}
}