matplot.cpp

用神经网络对系统辨识(BP网络)。此程序为c语言和matlab混和编程

#include "matplot.h"
#include "stdlib.h"
#include "engine.h"
#include "system.h"
#include <memory.h>

void matDraw( double ridArray[], double rteArray[],double yidArray[], double yteArray[], double ydiArray[], double ydtArray[] ) 
{
	Engine* ep;
	mxArray* rid;//学习信号
	mxArray* rte;//测试信号
	mxArray* yid;//学习网络输出
	mxArray* yte;//测试网络输出
	mxArray* ydi;//学习期望输出
	mxArray* ydt;//测试期望输出

    //打开引擎
	if(  !( ep= engOpen(NULL) )  )
		printf("cannot open the engine!");
    
	//构建各矩阵值
	rid = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy( (void*) mxGetPr( rid ), (void*) ridArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "rid", rid );

	rte = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy( (void*) mxGetPr( rte ), (void*) rteArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "rte", rte );

	yid = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy( (void*) mxGetPr( yid ), (void*) yidArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "yid", yid );

	yte = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy( (void*) mxGetPr( yte ),(void*) yteArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "yte", yte );

	ydi = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy( (void*) mxGetPr( ydi ), (void*) ydiArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "ydi", ydi );

	ydt = mxCreateDoubleMatrix(1, IDEN, mxREAL);
	memcpy((void*) mxGetPr( ydt ), (void*) ydtArray, IDEN*sizeof(double)  );
	engPutVariable( ep, "ydt", ydt );


	//画图
	engEvalString(ep, "t= [0:0.1:1.9];");
	engEvalString(ep, "plot(t, rid);");
	engEvalString(ep, "title('辨识信号');");
	engEvalString(ep, "xlabel('t');");
    engEvalString(ep, "ylabel('rid');");

	engEvalString(ep, "figure;");
	engEvalString(ep, "t= [0:0.1:1.9];");
	engEvalString(ep, "plot(t, rte);");
	engEvalString(ep, "title('测试信号');");
	engEvalString(ep, "xlabel('t');");
	engEvalString(ep, "ylabel('rte');");

	engEvalString(ep, "figure;");
	engEvalString(ep, "t= [0:0.1:1.9];");
	engEvalString(ep, "plot( t, ydi,'r*-',t, yid,'r+:');");
	engEvalString(ep, "title('辨识期望输出及网络学习输出');");
	engEvalString(ep, "xlable('t');");
	engEvalString(ep, "ylable('ydi yid');");
	engEvalString(ep, "legend('* 期望输出','+ 学习输出');");

	engEvalString(ep, "figure;");
	engEvalString(ep, "t= [0:0.1:1.9];");
	engEvalString(ep, "plot(t, ydt,'r*-', t, yte,'r+:' );");
	engEvalString(ep, "title('测试期望输出及网络学习输出');");
	engEvalString(ep, "xlabel('t');");
	engEvalString(ep, "ylabel('ydt yte');");
	engEvalString(ep, "legend('* 期望输出','+ 学习输出');");
    
	getchar();
    //关闭引擎
	engClose( ep );
}