Package tv.floe.metronome.classification.neuralnetworks.activation

Examples of tv.floe.metronome.classification.neuralnetworks.activation.ActivationFunction


        neuron.setError( 0 );
                x++;
        continue;
      }
     
      ActivationFunction transferFunction = neuron.getActivationFunction();
      double neuronInput = neuron.getNetInput();
      double delta = outputError[ x ] * transferFunction.getDerivative( neuronInput ); // delta = (d-y)*df(net)
      neuron.setError( delta );
                       
      this.updateNeuronWeights( neuron );       
      x++;
     
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        neuron.setError( 0 );
                x++;
        continue;
      }
     
      ActivationFunction transferFunction = neuron.getActivationFunction();
      double neuronInput = neuron.getNetInput();
      double delta = outputError[ x ] * transferFunction.getDerivative( neuronInput ); // delta = (d-y)*df(net)
      neuron.setError( delta );
                       
      this.updateNeuronWeights( neuron );       
      x++;
     
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    } // for

   
   
    ActivationFunction transferFunction = neuron.getActivationFunction();
   
   
    double netInput = neuron.getNetInput(); // should we use input of this or other neuron?
    double fnDerv = transferFunction.getDerivative(netInput);
    double neuronError = fnDerv * deltaSum;
    return neuronError;
 
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  public static Neuron createNeuron(Config c, int layerIndex) {
   
    Neuron n = null;
    ActivationFunction tf = null;
   
    if (0 == layerIndex) {
      n = new InputNeuron();
     
    } else {
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  public static Neuron createNeuron(Config c, int layerIndex) {
   
    Neuron n = null;
    ActivationFunction tf = null;
   
    if (0 == layerIndex) {
      n = new InputNeuron();
     
    } else {
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