somnet.h

一个可以运行的som神经网络程序

// Somnet.h: interface for the CSomnet class.
//
//////////////////////////////////////////////////////////////////////

#if !defined(AFX_SOMNET_H__6EA27563_6E24_4738_A619_BDD9B96C786B__INCLUDED_)
#define AFX_SOMNET_H__6EA27563_6E24_4738_A619_BDD9B96C786B__INCLUDED_

#if _MSC_VER > 1000
#pragma once
#endif // _MSC_VER > 1000



/*#define InputLayerNum 35*/
#define OutputLayerRow 8
#define OutputLayerColumn 12
#define total_iteration_Num 80//10000//80//100//1000
#define error_limit 0.0000000000008//0.1//0.0000000000008//0.000000000000008//0.0001
#define efficiency 0.9//0.3//0.9//0.3//0.9

class CSomnet  
{
int layernumber,ndnumber;
int InputLayerNum;
double **inputMode;
double **weight;
int current_iteration_num;
double study_efficiency;
long double distance[OutputLayerRow*OutputLayerColumn];
int neighbor_width;
int neighbor_height;
int row[OutputLayerRow],column[OutputLayerColumn];
int flag[OutputLayerRow][OutputLayerColumn];
int temp_row,temp_column;
int winner_row,winner_column;
long double min_distance;
public:
	CSomnet();
	CSomnet(int layer,int nd);
	virtual ~CSomnet();
	void init_distance();
	void eula_distance(int z);
	void weight_change(int z);
	void paraChange();
	void initialize();
	void test_netWork_1();
	void test_netWork_2();
	int getcurrentnum();
	long double getmindistance();
	void Treatnet();


};

#endif // !defined(AFX_SOMNET_H__6EA27563_6E24_4738_A619_BDD9B96C786B__INCLUDED_)