/// <summary> /// Creates a new Kohonen SOM, with the specified input and output layers. (You are required /// to connect all layers using appropriate synapses, before using the constructor. Any changes /// made to the structure of the network here-after, may lead to complete malfunctioning of the /// network) /// </summary> /// <param name="inputLayer"> /// The input layer /// </param> /// <param name="outputLayer"> /// The output layer /// </param> /// <exception cref="ArgumentNullException"> /// If <c>inputLayer</c> or <c>outputLayer</c> is <c>null</c> /// </exception> public KohonenNetworkND(ILayer inputLayer, KohonenLayerND outputLayer) : base(inputLayer, outputLayer, TrainingMethod.Unsupervised) { }
/// <summary> /// Creates new position neuron in n-dimensional space /// </summary> /// <param name="posVector"> /// Vector that defines the position of the neuron /// <param name="parent"> /// Parent layer containing this neuron /// </param> /// <exception cref="ArgumentNullException"> /// If <c>parent</c> is <c>null</c> /// </exception> public PositionNeuron(int[] posVector, KohonenLayerND parentND) { this.coordinateND = posVector; this.parentND = parentND; }