短时FRFT的MATLAB代码
时间: 2023-06-15 14:08:04 浏览: 143
短时FRFT是一种时间-频率分析方法,可以对非平稳信号进行分析。下面是MATLAB代码示例:
```matlab
% 设置参数
alpha = 0.5; % FRFT参数
N = 1024; % 信号长度
h = hamming(N); % 窗函数
M = 64; % 分析时间窗口长度
L = 32; % 分析时间窗口重叠长度
% 生成测试信号
t = linspace(0, 1, N);
x = sin(2*pi*100*t) .* (1 + 0.5*sin(2*pi*10*t));
% 计算短时FRFT
for i = 1:M-L:N-M+1
xw = x(i:i+M-1) .* h; % 应用窗函数
y = frft(xw, alpha); % 计算FRFT
Y(:,i) = y; % 存储结果
end
% 绘制结果
t = linspace(0, 1, size(Y, 2));
f = linspace(-0.5, 0.5, N);
imagesc(t, f, abs(Y).^2);
axis xy;
xlabel('时间');
ylabel('频率');
```
其中,`frft`是实现FRFT的函数,可以从MATLAB File Exchange下载到。此代码将生成一个时间-频率图,表示信号在时间和频率上的分布情况。
相关问题
FrFT matlab
The Fractional Fourier Transform (FrFT) is a generalization of the traditional Fourier transform that allows for variable rotation of the signal in the time-frequency plane. It has applications in signal processing, image processing, and communication systems.
In MATLAB, the FrFT can be computed using the "frft" function in the Signal Processing Toolbox. The syntax for the function is:
y = frft(x, alpha)
where "x" is the input signal, and "alpha" is the rotation angle in radians. The output "y" is the FrFT of "x" with rotation angle "alpha".
Here is an example code that computes the FrFT of a signal "x" with rotation angle "alpha":
% Create a signal
n = 0:99;
x = sin(2*pi*0.1*n) + sin(2*pi*0.2*n) + sin(2*pi*0.3*n);
% Compute the FrFT
alpha = 0.5; % Rotation angle
y = frft(x, alpha);
% Plot the original and FrFT signals
subplot(2,1,1);
plot(n, x);
title('Original signal');
xlabel('Sample index');
ylabel('Amplitude');
subplot(2,1,2);
plot(n, y);
title(['FrFT with alpha=' num2str(alpha)]);
xlabel('Sample index');
ylabel('Amplitude');
This code generates a plot that shows the original signal and its FrFT with a rotation angle of 0.5 radians. You can modify the rotation angle and the input signal to experiment with different FrFT results.
短时分数阶傅里叶变换matlab代码
短时分数阶傅里叶变换(short-time fractional Fourier transform)是将传统的傅里叶变换(Fourier transform)推广到分数阶傅里叶变换(fractional Fourier transform)的框架下的一种信号处理方法。在MATLAB中,可以使用Signal Processing Toolbox中的`frft`函数实现短时分数阶傅里叶变换。下面是一段示例代码:
```matlab
% 生成测试信号
t = linspace(-1, 1, 1024);
x = exp(-50 * t.^2) .* cos(2 * pi * 16 * t);
% 设定分数阶参数和窗口长度
alpha = 0.5;
win_len = 128;
% 生成窗口函数
win = hamming(win_len);
% 计算短时分数阶傅里叶变换
nfft = 2^nextpow2(win_len);
hop_len = win_len / 2;
st_frft = zeros(win_len, length(t));
for i = 1:length(t)
if (i-1)*hop_len+win_len <= length(x)
x_win = x((i-1)*hop_len+1:(i-1)*hop_len+win_len) .* win;
st_frft(:, i) = frft(x_win, alpha, nfft);
else
break
end
end
% 绘制短时分数阶傅里叶变换的时频图
figure
imagesc(abs(st_frft))
axis xy
colormap(jet)
xlabel('Time')
ylabel('Frequency')
title('Short-time Fractional Fourier Transform')
```
在上述代码中,首先生成了一个测试信号,然后设定了分数阶参数和窗口长度。接着生成了一个汉明窗口,并利用循环计算了短时分数阶傅里叶变换。最后绘制了短时分数阶傅里叶变换的时频图。