www.pudn.com > bp_cpp.zip > bpneuron.h

#ifndef _PUBLIC_ANN_BP_BPNEURON_H 
#define _PUBLIC_ANN_BP_BPNEURON_H 
/* 
 * public/ann/bp/bpneuron.h 
 * 2004-2-16 by ShanLanshan 
 */ 
 
#include "public/ann/annbase.h" 
#include "public/ann/neuron.h" 
#include "public/ann/neuron_group.h" 
#include "public/ann/interface.h" 
 
namespace ann { 
 
class BPNeuron;		// BP网络神经元 
class BPLayer;		// BP网络层 
class BPNet;		// BP网络 
 
// 定义BP网络神经元类 
class BPNeuron: public Neuron { 
protected: 
	//ann_int		m_layer;			/* 当前层数 */ 
	ann_float	m_deviation;		/* 当前节点偏差 */ 
public: 
	BPNeuron(); 
	virtual ~BPNeuron(); 
	inline void learn_tutor(ann_float t, bool back_pass); 
	inline void learn_deviation(bool back_pass); 
	inline void prepair_learn() {m_deviation = ANN_FLOAT_ZERO;}; 
	//virtual void respond(); 
	//virtual void output(); 
}; 
 
// 定义BP网络神经元层的类 
class BPLayer: public NeuronSimpleGroup, public ISerialObj { 
protected: 
	enum BPLayerType {INPUT_LAYER, HIDDEN_LAYER, OUTPUT_LAYER}; 
	enum LearnType {DERIVATIVE, GRADIENT};	// 学习算法：导数下降/梯度下降，教科书上是导数下降 
	BPLayerType m_type; 
	ann_int m_height; 
	ann_int m_learn_type; 
	ann_int m_size; 
	bool m_inited; 
	BPNeuron m_fix_neuron; 
public:	// method of ISerialObj 
	virtual ostream& operator >>(ostream &os); 
	virtual istream& operator <<(istream &is); 
public: 
	BPLayer(); 
	virtual ~BPLayer(); 
	bool init(ann_int size); 
	inline ann_int get_size() {return m_size;}; 
	void prepair_learn(); 
	virtual bool mutual_conn(BPLayer *b); 
	virtual bool get_vector(IAnnVector *vec); 
	virtual void output(); 
}; 
 
class BPLayerInput: public BPLayer { 
public: 
	BPLayerInput(){m_type = INPUT_LAYER;}; 
	virtual bool set_vector(IAnnVector *vec); 
}; 
 
class BPLayerOutput: public BPLayer { 
public: 
	BPLayerOutput(){m_type = OUTPUT_LAYER;}; 
	virtual int learn_tutor(IAnnVector *vec, bool back_pass); 
}; 
 
class BPLayerHidden: public BPLayer { 
public: 
	BPLayerHidden() {m_type = HIDDEN_LAYER;}; 
	virtual int learn_deviation(bool back_pass); 
}; 
 
// 定义BP神经元网络类 
class BPNet:  
	public NeuronGroup, 
	public IAnnVectorConverter, 
	public ISerialObj { 
protected: 
	int m_layer_count; 
	ann_int m_learn_count; 
	ann_int m_convert_count; 
	BPLayer **m_layer; 
	BPLayerInput *m_layer_input;		// 指向输入层的指针 
	BPLayerOutput *m_layer_output;		// 指向输出层的指针 
public:	// method of ISerialObj 
	virtual ostream& operator >>(ostream &os); 
	virtual istream& operator <<(istream &is); 
public: 
	BPNet(); 
	virtual ~BPNet(); 
	bool mutual_conn(); 
	bool init(const char *s);	// s like this: "1024 * 12 * 4" 
	bool init(int a[], int len); 
	void random();	// 随机化网络初始值 
	void set_output_func(AnnFuncGroup *fg, int layer = -1); 
	inline ann_int get_layer_size(ann_int layer) { 
		assert(layer >= 0); 
		assert(layer < m_layer_count); 
		assert(m_layer != NULL); 
		assert(m_layer[layer] != NULL); 
		return m_layer[layer]->get_size(); 
	}; 
	inline ann_int get_layer_count() {return m_layer_count;}; 
	inline ann_int get_input_division() {return get_layer_size(0);}; 
	inline ann_int get_output_division() {return get_layer_size(get_layer_count() - 1);}; 
	inline ann_int get_interface_division() {return get_input_division() + get_output_division();}; 
public: // interface of IAnnVectorConverse 
	virtual bool set_input(IAnnVector *vecin); 
	virtual bool get_output(IAnnVector *vecout); 
	virtual bool learn(IAnnVector *vecout); 
	virtual bool convert(); 
}; 
 
	// global functions 
	extern bool set_bp_learn_rate(ann_float rate); 
	extern ann_float get_bp_learn_rate(); 
 
} 
 
#endif /* !_PUBLIC_ANN_BP_BPNEURON_H */