mirror of
https://github.com/hanzoai/jube-fork.git
synced 2026-10-30 18:33:33 +00:00
richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
143 lines
3.9 KiB
C#
143 lines
3.9 KiB
C#
// AForge Neural Net Library
|
|
// AForge.NET framework
|
|
// http://www.aforgenet.com/framework/
|
|
//
|
|
// Copyright � AForge.NET, 2007-2012
|
|
// [email protected]
|
|
//
|
|
|
|
namespace Accord.Neuro
|
|
{
|
|
using System;
|
|
using AForge;
|
|
using Accord;
|
|
using Accord.Math.Random;
|
|
using Accord.Statistics.Distributions.Univariate;
|
|
using Accord.Compat;
|
|
|
|
/// <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>
|
|
///
|
|
[Serializable]
|
|
public abstract class Neuron
|
|
{
|
|
/// <summary>
|
|
/// Neuron's inputs count.
|
|
/// </summary>
|
|
protected int inputsCount = 0;
|
|
|
|
/// <summary>
|
|
/// Neuron's weights.
|
|
/// </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 IRandomNumberGenerator<double> rand =
|
|
new UniformContinuousDistribution();
|
|
|
|
/// <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 IRandomNumberGenerator<double> RandGenerator
|
|
{
|
|
get { return rand; }
|
|
set { rand = value; }
|
|
}
|
|
|
|
|
|
/// <summary>
|
|
/// Neuron's inputs count.
|
|
/// </summary>
|
|
public int InputsCount
|
|
{
|
|
get { return inputsCount; }
|
|
set { inputsCount = value; }
|
|
}
|
|
|
|
/// <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; }
|
|
set {} //Not Implemented.
|
|
}
|
|
|
|
|
|
/// <summary>
|
|
/// Neuron's weights.
|
|
/// </summary>
|
|
public double[] Weights
|
|
{
|
|
get { return weights; }
|
|
set {weights = 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>
|
|
///
|
|
protected 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 specified
|
|
/// by the <see cref="RandGenerator"/>.</remarks>
|
|
///
|
|
public virtual void Randomize()
|
|
{
|
|
rand.Generate(weights.Length, weights);
|
|
}
|
|
|
|
/// <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);
|
|
}
|
|
}
|