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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.
81 lines
3.0 KiB
C#
81 lines
3.0 KiB
C#
// AForge Neural Net Library
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// AForge.NET framework
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// http://www.aforgenet.com/framework/
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//
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// Copyright © AForge.NET, 2007-2012
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// [email protected]
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//
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namespace Accord.Neuro
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{
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using System;
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using Accord.Compat;
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/// <summary>
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/// Distance neuron.
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/// </summary>
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///
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/// <remarks><para>Distance neuron computes its output as distance between
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/// its weights and inputs - sum of absolute differences between weights'
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/// values and corresponding inputs' values. The neuron is usually used in Kohonen
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/// Self Organizing Map.</para></remarks>
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///
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[Serializable]
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public class DistanceNeuron : Neuron
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{
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/// <summary>
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/// Initializes a new instance of the <see cref="DistanceNeuron"/> class.
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/// </summary>
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///
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/// <param name="inputs">Neuron's inputs count.</param>
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///
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public DistanceNeuron( int inputs ) : base( inputs ) { }
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/// <summary>
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/// Computes output value of neuron.
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/// </summary>
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///
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/// <param name="input">Input vector.</param>
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///
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/// <returns>Returns neuron's output value.</returns>
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///
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/// <remarks><para>The output value of distance neuron is equal to the distance
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/// between its weights and inputs - sum of absolute differences.
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/// The output value is also stored in <see cref="Neuron.Output">Output</see>
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/// property.</para>
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///
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/// <para><note>The method may be called safely from multiple threads to compute neuron's
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/// output value for the specified input values. However, the value of
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/// <see cref="Neuron.Output"/> property in multi-threaded environment is not predictable,
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/// since it may hold neuron's output computed from any of the caller threads. Multi-threaded
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/// access to the method is useful in those cases when it is required to improve performance
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/// by utilizing several threads and the computation is based on the immediate return value
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/// of the method, but not on neuron's output property.</note></para>
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/// </remarks>
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///
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/// <exception cref="ArgumentException">Wrong length of the input vector, which is not
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/// equal to the <see cref="Neuron.InputsCount">expected value</see>.</exception>
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///
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public override double Compute( double[] input )
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{
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// check for corrent input vector
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if ( input.Length != inputsCount )
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throw new ArgumentException( "Wrong length of the input vector." );
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// difference value
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double dif = 0.0;
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// compute distance between inputs and weights
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for ( int i = 0; i < inputsCount; i++ )
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{
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dif += Math.Abs( weights[i] - input[i] );
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}
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// assign output property as well (works correctly for single threaded usage)
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this.output = dif;
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return dif;
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}
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}
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}
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