sigma=0.2; x_g=zeros(100,1)'; for j=1:100 dist=sqrt((x0(j))^2); x_g(j)=exp(-(dist)/2*sigma^2);%gauss %x_g(j,k)=((dist)^2+1)^0.5; end w=x_g\z0'; x_hat = linspace(-2, 2, 100);，在代码中替换w=x_g\z0'

根据您提供的代码，可以看出w=x_g\z0'是将x_g矩阵左除以z0'向量得到的结果，可以使用MATLAB中的inv函数或者/运算符来替换。具体来说，可以使用以下两种方式替换：

1.使用inv函数：

w = inv(x_g) * z0';

2.使用/运算符：

w = x_g / z0';

以上两种方式的效果应该是一样的，您可以根据自己的习惯选择使用哪种方式。希望能够帮助到您。

相关问题

修正代码：clear x= linspace(-2, 2, 100); y= linspace(-2, 2, 100); nx=length(x); ny=length(y); for i=1:nx for j=1:ny f(i,j)=franke([x(i) y(j)]); end end figure(1) mesh(x,y,f) title('原始曲面') k=1; r1=linspace(-2, 2, 10); s1=linspace(-2, 2, 10); for i=1:length(r1) for j=1:length(s1) M(k,:)=[r1(i) s1(j)];%M中是均匀采样点的坐标 k=k+1; end end m=size(M,1); for k=1:m MV(k)=franke(M(k,:));%采样点相应的函数值 end figure(4)%画出均匀采样点 for i=1:m plot(M(i,1),M(i,2),'.') hold on end title('均匀采样点') %计算系数矩阵 %RBF sigma=0.2; x_g=zeros(100,100); for j=1:100 for k=1:100 dist=sqrt((r1(j)-r1(k))^2+(s1(j)-s1(k))^2); x_g(j,k)=exp(-(dist)/2*sigma^2);%gauss %x_g(j,k)=((dist)^2+1)^0.5; end end d=x_g\MV';

修正后的代码如下：

clear
x = linspace(-2, 2, 100);
y = linspace(-2, 2, 100);
nx = length(x);
ny = length(y);
for i = 1:nx
    for j = 1:ny
        f(i,j) = franke([x(i) y(j)]);
    end
end
figure(1)
mesh(x,y,f)
title('原始曲面')

k = 1;
r1 = linspace(-2, 2, 10);
s1 = linspace(-2, 2, 10);
for i = 1:length(r1)
    for j = 1:length(s1)
        M(k,:) = [r1(i) s1(j)]; % M中是均匀采样点的坐标
        k = k+1;
    end
end
m = size(M,1);
figure(2)
for i = 1:m
    plot(M(i,1),M(i,2),'.')
    hold on
end
title('均匀采样点')

% 计算系数矩阵
% RBF sigma=0.2;
x_g = zeros(m,m);
for j = 1:m
    for k = 1:m
        dist = sqrt((M(j,1)-M(k,1))^2 + (M(j,2)-M(k,2))^2);
        x_g(j,k) = exp(-(dist)^2/(2*sigma^2)); % gauss
        % x_g(j,k) = ((dist)^2+1)^0.5;
    end
end
d = x_g\MV';

修正点：

1. 修正了计算系数矩阵时，距离计算公式的错误。
2. 修正了画均匀采样点的代码错误，将 figure(4) 改为 figure(2)。

将代码转化为画二维图形的代码：x0=zeros(100,1)'; y0=zeros(100,1)'; z0=zeros(100,1)'; k=1 x1= linspace(-2, 2, 10); y1= linspace(-2, 2, 10); for i = 1:length(x1) for j = 1:length(y1) M(k,:) = [x1(i) y1(j)]; % M中是均匀采样点的坐标 k = k+1; end end x0 = M(:, 1); % 提取 M 的第一列，即 x1 列 y0 = M(:, 2); % 提取 M 的第二列，即 y1 列 for i = 1:100 z0(i) = sin(pix0(i)/2) + cos(pix0(i)/3); end figure(1); plot3(x0,y0,z0,''); %RBF sigma=0.2; x_g=zeros(100,100); for j=1:100 for k=1:100 dist=sqrt((x0(j)-x0(k))^2+(y0(j)-y0(k))^2); x_g(j,k)=exp(-(dist)/2sigma^2);%gauss %x_g(j,k)=((dist)^2+1)^0.5; end end w=x_g\z0'; x_hat = linspace(-2, 2, 100); y_hat = linspace(-2, 2, 100); z_g=zeros(length(x_hat),length(x_hat)); for p=1:length(x_hat) for n=1:length(x_hat) for m=1:100 dist2=sqrt((x0(m)-x_hat(p))^2+(y0(m)-y_hat(n))^2); f=w(m)exp(-(dist2)/2sigma^2);%gauss %f=w(m)*((dist2)^2+1)^0.5; z_g(p,n)=z_g(p,n)+f; end z_real=x_hat(p)exp(-x_hat(p)^2+y_hat(n)); end end figure(2) mesh(x_hat,y_hat,z_g'); %set(gcf, 'Renderer', 'ZBuffer'); axis([-2 2 -2 2 -2 2]); E_max=max(max(abs(z_g-z_real))); E_avg=mean(mean(abs(z_g-z_real))); fprintf('均方根误差最大值为 %.4f\n', E_max) fprintf('均方根误差平均值为 %.4f\n', E_avg) x = [1]; y1 = E_max; y2 =E_avg; % 绘制第一组数据的图形，使用红色实线 figure(3) plot(x, y2, ''); hold on;

好的，以下是将代码转化为画二维图形的代码：

% 均匀采样点
x0 = zeros(100, 1)';
y0 = zeros(100, 1)';
z0 = zeros(100, 1)';
k = 1;
x1 = linspace(-2, 2, 10);
y1 = linspace(-2, 2, 10);
for i = 1:length(x1)
    for j = 1:length(y1)
        M(k,:) = [x1(i) y1(j)]; % M中是均匀采样点的坐标
        k = k + 1;
    end
end
x0 = M(:, 1); % 提取 M 的第一列，即 x1 列 
y0 = M(:, 2); % 提取 M 的第二列，即 y1 列 

% 真实函数
for i = 1:100
    z0(i) = sin(pi*x0(i)/2) + cos(pi*x0(i)/3);
end

% 绘制均匀采样点和真实函数的图像
figure(1);
plot3(x0, y0, z0, '');

% RBF插值
sigma = 0.2;
x_g = zeros(100, 100);
for j = 1:100
    for k = 1:100
        dist = sqrt((x0(j)-x0(k))^2 + (y0(j)-y0(k))^2);
        x_g(j, k) = exp(-dist/2/sigma^2); % 高斯核函数
        %x_g(j, k) = ((dist)^2 + 1)^0.5; % 多项式核函数
    end
end
w = x_g \ z0';
x_hat = linspace(-2, 2, 100);
y_hat = linspace(-2, 2, 100);
z_g = zeros(length(x_hat), length(x_hat));
for p = 1:length(x_hat)
    for n = 1:length(x_hat)
        for m = 1:100
            dist2 = sqrt((x0(m)-x_hat(p))^2 + (y0(m)-y_hat(n))^2);
            f = w(m) * exp(-dist2/2/sigma^2); % 高斯核函数
            %f = w(m) * ((dist2)^2 + 1)^0.5; % 多项式核函数
            z_g(p, n) = z_g(p, n) + f;
        end
        z_real = x_hat(p) * exp(-x_hat(p)^2 + y_hat(n));
    end
end

% 绘制插值结果的图像
figure(2)
mesh(x_hat, y_hat, z_g');
%set(gcf, 'Renderer', 'ZBuffer');
axis([-2 2 -2 2 -2 2]);

% 计算误差并输出
E_max = max(max(abs(z_g-z_real)));
E_avg = mean(mean(abs(z_g-z_real)));
fprintf('均方根误差最大值为 %.4f\n', E_max)
fprintf('均方根误差平均值为 %.4f\n', E_avg)

% 绘制误差图像
x = [1];
y1 = E_max;
y2 = E_avg;
figure(3)
plot(x, y2, '');
hold on;