%======================================================================
        % Copyright (C) 2005
        % All rights reserved.

        % File name: Polynomial.m 
        % Notes:     應(yīng)用RBF網(wǎng)絡(luò)對(duì) Polynomial 進(jìn)行函數(shù)逼近
        %            檢驗(yàn)反向傳播的逼近效果
        %            最簡(jiǎn)單的簡(jiǎn)單的梯度下降算法

        % Version: 1.0
        % Author:  bug zhang
        % Date:    2005.1
        %======================================================================        
        
        close all	%關(guān)閉所有的窗口
        clear all	%清除所有的變量
        k=input('訓(xùn)練集點(diǎn)數(shù)=k,k=[3000]   ');
        if isempty(k),
           k=3000;
        end;
        L=input('最大隱層神經(jīng)元個(gè)數(shù)=L,L=[15]   ');
        if isempty(L),
           L=15;
        end;
        S=input('歸一化參數(shù)=S,S=[1]   ');
        if isempty(S),
           S=1;
        end;

        X=rand(1,k);
        Y=1+2.*X+3.*X.^2+4.*X.^3+5.*X.^4;
        
       
        net=newrb(X,Y,0.01,S,L,1);
        
        X2=linspace(0,1,1000);
        Y2=1+2.*X2+3.*X2.^2+4.*X2.^3+5.*X2.^4;
        
        X1=rand(1,30);
        Y1=1+2.*X1+3.*X1.^2+4.*X1.^3+5.*X1.^4;
        R=sim(net,X1);
        
        G=linspace(min(Y1),max(Y1),1000);
        T=G;
        
        figure(1)
        plot(X2,Y2,'-k',X1,R,'.b',X1,Y1,'+r')
        grid on
        xlabel('x in [0,10]')
        ylabel('y=sin(x).*exp(-x)')
        title('簡(jiǎn)單bp網(wǎng)絡(luò)應(yīng)用于函數(shù)逼近')
        
        figure(2)
        plot(G,T,'-k',R,Y1,'+r')