短时傅里叶实现对信号处理matlab代码并输出前后的频谱图

以下是一个使用 Matlab 实现短时傅里叶变换对信号进行处理的示例代码，并输出前后的频谱图：

% 读取音频信号
[y, Fs] = audioread('audio_file.wav');

% 定义窗口长度和重叠长度
win_len = 1024;
overlap = win_len/2;

% 对信号进行分帧
frame_len = win_len;
num_frames = floor(length(y)/(frame_len-overlap));
frames = zeros(frame_len, num_frames);

for i = 1:num_frames
    start_idx = (i-1)*(frame_len-overlap)+1;
    end_idx = start_idx+frame_len-1;
    frames(:,i) = y(start_idx:end_idx);
end

% 对每一帧进行短时傅里叶变换
S = [];
for i = 1:num_frames
    [s, f, t] = spectrogram(frames(:,i), win_len, overlap, win_len, Fs);
    S = [S s];
end

% 输出前后的频谱图
subplot(2,1,1);
imagesc(abs(S));
colorbar;
xlabel('Time (s)');
ylabel('Frequency (Hz)');
title('Before Short-Time Fourier Transform');

% 对每一帧的频谱进行平滑
for i = 1:num_frames
    start_idx = (i-1)*size(f,1)+1;
    end_idx = i*size(f,1);
    S(:,start_idx:end_idx) = smoothdata(S(:,start_idx:end_idx), 'movmean', 3);
end

% 输出处理后的频谱图
subplot(2,1,2);
imagesc(abs(S));
colorbar;
xlabel('Time (s)');
ylabel('Frequency (Hz)');
title('After Short-Time Fourier Transform');

在代码中，`audioread`函数用于读取音频信号，`spectrogram`函数用于对每一帧进行短时傅里叶变换。在分帧后，对每一帧的频谱进行平滑处理，可以使用`smoothdata`函数进行平滑处理。最后，通过`imagesc`函数输出前后的频谱图。