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📄 simpleneuron.h

📁 C++神经网络开发包ANNIE
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#ifndef _SIMPLENEURON_H#define _SIMPLENEURON_H#include "AbstractNeuron.h"#include "defines.h"namespace annie{/** A simple perceptron - i.e., it takes as input the weighted sum of the  * outputs of the neurons connected to it.  * Probably the first type of neuron you would come across in any   * introductory literature of neural networks.  */class SimpleNeuron : public AbstractNeuron{protected:	/// The derivative of the activation function, required for gradient descent training	ActivationFunction _dActivationFunction;	/// @see Neuron::_recacheOutput	virtual void _recacheOutput() const;	/// @see Neuron::_recacheError	virtual void _recacheError() const;public:	/** Creates a simple neuron with the given label.	  * @param label The label to be given to the neuron	  * @param hasBias true if the neuron is allowed to have a bias, false otherwise. Default is true	  * @see removeBias	  */	SimpleNeuron(int label, bool hasBias = true);	/** Sets the desired output of the neuron.	  * Should be called only for output neurons, i.e., those whose output is not	  * connected to anyone else. Setting the desired output at these neurons	  * will form the basis of error backpropagation	  * @param desired The desired output of this neuron	  * @throws Exception if the neuron is not an output neuron	  */	virtual void setDesiredOutput(real desired);	/** Sets the activation function and its derivative (required for error backpropagation)	  * @param f The activation function to be used	  * @param df The derivative of the activation function	  */	virtual void setActivationFunction(ActivationFunction f, ActivationFunction df);	/// Returns "SimpleNeuron"	virtual const char *getClassName() const;};}; //namespace annie#endif // define _SIMPLENEURON_H

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