www.pudn.com > neuroocr_src.zip > Neuron.cs

// AForge Neural Net Library 
// 
// Copyright © Andrew Kirillov, 2005 
// andrew.kirillov@gmail.com 
// 
 
namespace AForge.NeuralNet 
{ 
	using System; 
 
	/// 
 
	/// Neuron 
	/// 
 
	public class Neuron 
	{ 
		protected int		inputsCount = 1; 
		protected float[]	weights = new float[1];	// synapses weights 
		protected float		threshold = 0.0f; 
		protected IActivationFunction	function = new SigmoidFunction(); 
 
		protected float		sum;		// weighted input's sum 
		protected float		output;		// neuron's output value 
 
		protected static Random	rand = new Random(); 
 
		// Inputs count property 
		public int InputsCount 
		{ 
			get { return inputsCount; } 
			set 
			{ 
				inputsCount = Math.Max(1, value); 
				weights = new float[inputsCount]; 
			} 
		} 
		// Threshold property 
		public float Threshold 
		{ 
			get { return threshold; } 
			set { threshold = value; } 
		} 
		// Activation function property 
		public IActivationFunction ActivationFunction 
		{ 
			get { return function; } 
			set { function = value; } 
		} 
		// Output value 
		public float Output 
		{ 
			get { return output; } 
		} 
		// Get/Set weight value 
		public float this[int index] 
		{ 
			get { return weights[index]; } 
			set { weights[index] = value; } 
		} 
 
 
		// Constructors 
		public Neuron() 
		{ } 
		public Neuron(int inputs) : this(inputs, new SigmoidFunction()) 
		{ } 
		public Neuron(int inputs, IActivationFunction function) 
		{ 
			this.function = function; 
			InputsCount =  inputs; 
		} 
 
 
		// Compute the output value of the neuron 
		public float Compute(float[] input) 
		{ 
			if (input.Length != inputsCount) 
				throw new ArgumentException(); 
 
			sum = 0.0f; 
 
			// compute weighted sum of input 
			for (int i = 0; i < inputsCount; i++) 
			{ 
				sum += weights[i] * input[i]; 
			} 
			sum -= threshold; 
 
			return (output = function.Output(sum)); 
		} 
 
		// Randomize weights 
		public void Randomize() 
		{ 
			for (int i = 0; i < inputsCount; i++) 
				weights[i] = (float)(rand.NextDouble()); 
 
			threshold = (float)(rand.NextDouble()); 
		} 
	} 
}