clc clear close all n1=0:15; subplot(311) x1=[ones(1,8),zeros(1,3)]; y1=zeros(1,6); y1(2)=1; g1= conv(x1,y1); stem(n1, g1(n1+1)) title('序列卷积和结果'); grid on n2=0:20; subplot(312) x2=[ones(1,8),zeros(1,3)]; y2=[ones(1,8),zeros(1,3)]; g2= conv(x2,y2); stem(n

1, g2(n2+1)) title('序列卷积和结果'); grid on subplot(313) x3=[1,2,3,4]; h=[1,1,1]; y3=conv(x3,h); stem(0:length(y3)-1,y3) title('离散时间卷积结果'); grid on

请问，上面这段代码实现了什么功能？

相关问题

clc clear close all b = [0.0181,0.0543,0.0543,0.0181]; a = [1.0000,-1.7600,1.1829,-0.2781]; m = 0:length(b)-1; l = 0:length(a)-1; k = 0:500; w = (pi/500)*k; nume = b * exp(-j * m' * w); den = a * exp(-j * l' * w); H = nume ./ den; magH = abs(H); angH = angle(H); subplot(2,1,1); plot(w/pi,magH); title('Magnitude Response'); subplot(2,1,2); plot(w/pi,angH); title('Phase Response');对该代码进行注释说明

这段代码主要是实现了一个数字滤波器的频率响应的计算和绘图，具体注释如下：

clc; % 清空命令行窗口
clear; % 清空工作区变量
close all; % 关闭所有图形窗口

% 滤波器系数
b = [0.0181,0.0543,0.0543,0.0181];
a = [1.0000,-1.7600,1.1829,-0.2781];

% 构造频率向量
k = 0:500; % k为频率采样点数
w = (pi/500)*k; % 计算对应的频率值

% 计算滤波器的频率响应
m = 0:length(b)-1; % 求出分子多项式的次数
l = 0:length(a)-1; % 求出分母多项式的次数
nume = b * exp(-j * m' * w); % 计算分子多项式的频率响应
den = a * exp(-j * l' * w); % 计算分母多项式的频率响应
H = nume ./ den; % 计算滤波器的频率响应

% 绘制滤波器的频率响应曲线
magH = abs(H); % 计算幅频响应
angH = angle(H); % 计算相频响应
subplot(2,1,1); plot(w/pi,magH); title('Magnitude Response'); % 绘制幅频响应图
subplot(2,1,2); plot(w/pi,angH); title('Phase Response'); % 绘制相频响应图

总的来说，这段代码主要是用于计算和绘制数字滤波器的频率响应曲线，其中包括了幅频响应和相频响应。

补全代码：clear;clc % 读取图像文件 img = imread('Lena01.bmp'); img =imresize(img,0.2); % 显示原始图像 subplot(2, 2, 1); imshow(img); title('Original Image'); % 计算傅里叶变换 f = double(img); F = zeros(size(f)); [M, N] = size(f); for u = 0:M-1 for v = 0:N-1 for x = 0:M-1 for y = 0:N-1 end end end end % 显示傅里叶变换后的图像 subplot(2, 2, 2); imshow(log(1+abs(F)), []); title('Fourier Transform'); % 计算傅里叶逆变换 f2 = zeros(size(f)); for x = 0:M-1 for y = 0:N-1 for u = 0:M-1 for v = 0:N-1 end end end end

补全代码如下：

clear;clc % 读取图像文件
img = imread('Lena01.bmp');
img =imresize(img,0.2);

% 显示原始图像
subplot(2, 2, 1);
imshow(img);
title('Original Image');

% 计算傅里叶变换
f = double(img);
F = zeros(size(f));
[M, N] = size(f);
for u = 0:M-1
for v = 0:N-1
for x = 0:M-1
for y = 0:N-1
F(u+1, v+1) = F(u+1, v+1) + f(x+1, y+1) * exp(-2j*pi*((u*x/M)+(v*y/N)));
end
end
end
end

% 显示傅里叶变换后的图像
subplot(2, 2, 2);
imshow(log(1+abs(F)), []);
title('Fourier Transform');

% 计算傅里叶逆变换
f2 = zeros(size(f));
for x = 0:M-1
for y = 0:N-1
for u = 0:M-1
for v = 0:N-1
f2(x+1, y+1) = f2(x+1, y+1) + F(u+1, v+1) * exp(2j*pi*((u*x/M)+(v*y/N)));
end
end
end
end

% 显示傅里叶逆变换后的图像
subplot(2, 2, 3);
imshow(uint8(f2));
title('Inverse Fourier Transform');