Examples of eas.simulation.brain.neural.functions.ActivationFunction

Package eas.simulation.brain.neural.functions

Examples of eas.simulation.brain.neural.functions.ActivationFunction

eas.simulation.brain.neural.functions.ActivationFunction
Interface modeling the activation function Phi: R=> R of a neuron. Do not confuse with TransferFunction which models the computation of the weighted input of a neuron. (In literature the term transfer function is often referring to the activation function as well.) IMPORTANT: Activation functions are constrained to return values from [0, 1]. @author Lukas König

    }
    
    public void propagate() {
        this.neuronVector.mult(this.weightMatrix);
        for (int i = 0; i < this.neuronVector.getRowCount(); i++) {
            ActivationFunction act = this.getActivationFunction(i);
            this.neuronVector.set(0, i, act.activationPhi(this.neuronVector.get(0, i)));
        }
    }

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    public void propagateReverse() {
        if (this.inverseWeightMatrix == null) {
            this.createInverseWeightMatrix();
        }
        for (int i = 0; i < this.neuronVector.getRowCount(); i++) {
            ActivationFunction act = this.getActivationFunction(i);
            
            try {
                this.neuronVector.set(0, i, act.inverseActivationPhi(this.neuronVector.get(0, i)));
            } catch (InversionNotSupportedException e) {}
        }
        this.neuronVector.mult(this.inverseWeightMatrix);
    }

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    private void createInverseWeightMatrix() {
        this.inverseWeightMatrix = this.weightMatrix.inverse();
    }
    
    public ActivationFunction getActivationFunction(int neuronID) {
        ActivationFunction a = this.activationFunctions.get(neuronID);
        if (a == null) {
            return this.standardActFct;
        } else {
            return a;
        }

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