neuronetwork.h

我以前写的一个的神经网络学习函数逼近和分类的例子

//#if !defined(AFX_IGPC_NEURONETWORK_H_)
//#define AFX_IGPC_NEURONETWORK_H_

#define NEURONET_FUNCTYPE_LINEAR  0
#define NEURONET_FUNCTYPE_SIGMOID 1
#define NEURONET_FUNCTYPE_WAVELET 2


class CNeuroNet;


class CNeuron : public CObject
{
private:

protected:
	int m_iLayerNo;			//the layer index of this neuron
	int m_iWeightNum;		//number of weights of this neuron
	int m_iFunType;			//function type
	double* m_pWeights;		//weight array
	double m_dThreshold;	//threshold
	int m_iNo;				//index of this neuron in its layer
	CNeuroNet* m_pNet;

	double m_dError;		//backward error

public:
	double m_dInputSum;
	double m_dOutput;

	CNeuron(CNeuroNet* pNet, int iLayerNo, int iNo, double* pInitWeights, double dInitThreshold);
	CNeuron();
	~CNeuron();

	void Initialize(CNeuroNet* pNet, int iLayerNo, int iNo, double* pInitWeights, double dInitThreshold);
	void CalcInputSum();
	void CalcOutput();
	BOOL AdjustWeights();

};

//BP network
class CNeuroNet : public CObject
{
private:

protected:
	double* m_pInput;

public:
	CNeuron** m_Layers;		//2-D array point to each neuron
	int* m_pLayNodNum;		//each layer's neuron number
	int m_iLayNum;			//network's layer number
	int m_iMidLayFun;		//function of middle layer neurons
	int m_iOutLayFun;		//function of output layer neurons
	double m_dDelta;		//learning factor
	double* m_pExpOutput;	//expected output

	CNeuroNet();
	CNeuroNet(int* pLayNodNum, int iLayNum, int iMidLayFun, int iOutLayFun, double dDelta);
	~CNeuroNet();
	void GenerateInitWeights(double* pWeights, int iWeightNum);
	void SetInput(double* pInputVector);
	void SetExpOutput(double* pExpOutputVector);
	BOOL Train(int iTrainTimes);
	BOOL TrainOneTime();
	void ForwardCalc();
	BOOL BackwardCalc();
	void GetOutput(double* pOutputVector);
};

//交互传播网络
class CNeuronIT : public CNeuron
{
private:

protected:

public:
	BOOL AdjustWeights();
	BOOL NormalizeWeight();
	double CalcDistance();
};

class CNeuroNetIT : public CNeuroNet
{
private:

protected:

public:
	//CNeuronIT** m_Layers;		//2-D array point to each neuron

	//CNeuroNetIT();
	CNeuroNetIT(int iInLayNodNum, int iOutLayNodNum, double dDelta);
	~CNeuroNetIT();
	BOOL Train(int iTrainTimes);
	BOOL TrainOneTime();
	int GetWinNeuron();
	BOOL NormalizeVector(double* pVector, int iSize);
};


// #endif