Java Code Examples for org.neuroph.core.Layer#getNeuronsCount()
The following examples show how to use
org.neuroph.core.Layer#getNeuronsCount() .
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Example 1
Source File: KohonenLearning.java From NeurophFramework with Apache License 2.0 | 6 votes |
private void learnPattern(DataSetRow dataSetRow, int neighborhood) { neuralNetwork.setInput(dataSetRow.getInput()); neuralNetwork.calculate(); Neuron winner = getClosestNeuron(); if (winner.getOutput() == 0) return; // ako je vec istrenirana jedna celija, izadji Layer mapLayer = neuralNetwork.getLayerAt(1); int winnerIdx = mapLayer.indexOf(winner); adjustCellWeights(winner, 0); int cellNum = mapLayer.getNeuronsCount(); for (int p = 0; p < cellNum; p++) { if (p == winnerIdx) continue; if (isNeighbor(winnerIdx, p, neighborhood)) { Neuron cell = mapLayer.getNeuronAt(p); adjustCellWeights(cell, 1); } // if } // for }
Example 2
Source File: MatrixMlpLayer.java From NeurophFramework with Apache License 2.0 | 6 votes |
public MatrixMlpLayer(Layer sourceLayer, MatrixLayer previousLayer, TransferFunction transferFunction) { this.sourceLayer = sourceLayer; this.previousLayer = previousLayer; if (!(previousLayer instanceof MatrixInputLayer)) ((MatrixMlpLayer)previousLayer).setNextLayer(this); this.transferFunction = transferFunction; this.neuronsCount = sourceLayer.getNeuronsCount(); // if (sourceLayer.getNeuronAt(neuronsCount-1) instanceof BiasNeuron) this.neuronsCount = this.neuronsCount -1; this.inputsCount = previousLayer.getOutputs().length; outputs = new double[neuronsCount]; // biases = new double[neuronsCount]; // deltaBiases = new double[neuronsCount]; inputs = new double[inputsCount]; netInput = new double[neuronsCount]; weights = new double[neuronsCount][inputsCount]; deltaWeights = new double[neuronsCount][inputsCount]; errors = new double[neuronsCount]; copyNeuronsToMatrices(); }
Example 3
Source File: ConnectionFactory.java From NeurophFramework with Apache License 2.0 | 5 votes |
/** * Creates full connectivity within layer - each neuron with all other * within the same layer */ public static void fullConnect(Layer layer) { int neuronNum = layer.getNeuronsCount(); for (int i = 0; i < neuronNum; i++) { for (int j = 0; j < neuronNum; j++) { if (j == i) continue; Neuron from = layer.getNeuronAt(i); Neuron to = layer.getNeuronAt(j); createConnection(from, to); } // j } // i }
Example 4
Source File: ConnectionFactory.java From NeurophFramework with Apache License 2.0 | 5 votes |
/** * Creates full connectivity within layer - each neuron with all other * within the same layer with the specified weight values for all * conections. */ public static void fullConnect(Layer layer, double weightVal) { int neuronNum = layer.getNeuronsCount(); for (int i = 0; i < neuronNum; i++) { for (int j = 0; j < neuronNum; j++) { if (j == i) continue; Neuron from = layer.getNeuronAt(i); Neuron to = layer.getNeuronAt(j); createConnection(from, to, weightVal); } // j } // i }
Example 5
Source File: ConnectionFactory.java From NeurophFramework with Apache License 2.0 | 5 votes |
/** * Creates full connectivity within layer - each neuron with all other * within the same layer with the specified weight and delay values for all * conections. */ public static void fullConnect(Layer layer, double weightVal, int delay) { int neuronNum = layer.getNeuronsCount(); for (int i = 0; i < neuronNum; i++) { for (int j = 0; j < neuronNum; j++) { if (j == i) continue; Neuron from = layer.getNeuronAt(i); Neuron to = layer.getNeuronAt(j); createConnection(from, to, weightVal, delay); } // j } // i }
Example 6
Source File: ConnectionFactory.java From NeurophFramework with Apache License 2.0 | 3 votes |
/** * Creates forward connectivity pattern between the specified layers * * @param fromLayer * layer to connect * @param toLayer * layer to connect to */ public static void forwardConnect(Layer fromLayer, Layer toLayer, double weightVal) { for(int i=0; i<fromLayer.getNeuronsCount(); i++) { Neuron fromNeuron = fromLayer.getNeuronAt(i); Neuron toNeuron = toLayer.getNeuronAt(i); createConnection(fromNeuron, toNeuron, weightVal); } }
Example 7
Source File: ConnectionFactory.java From NeurophFramework with Apache License 2.0 | 3 votes |
/** * Creates forward connection pattern between specified layers * * @param fromLayer * layer to connect * @param toLayer * layer to connect to */ public static void forwardConnect(Layer fromLayer, Layer toLayer) { for(int i=0; i<fromLayer.getNeuronsCount(); i++) { Neuron fromNeuron = fromLayer.getNeuronAt(i); Neuron toNeuron = toLayer.getNeuronAt(i); createConnection(fromNeuron, toNeuron, 1); } }