MATLAB卡尔曼语音降噪程序示例，并画时域图和频域图

以下是一个MATLAB卡尔曼语音降噪程序的示例，同时附有时域图和频域图的绘制代码。

%% Load noisy speech signal
[x, fs] = audioread('noisy_speech.wav');

%% Define Kalman filter parameters
A = 1; % State transition matrix
H = 1; % Observation matrix
Q = 0.01; % Process noise covariance
R = 0.1; % Measurement noise covariance
P = 1; % Estimate error covariance
xhat = 0; % Initial state estimate
K = P*H'/(H*P*H' + R); % Kalman gain

%% Apply Kalman filter to noisy speech signal
y = zeros(length(x), 1);
for n = 1:length(x)
    xhat = A*xhat;
    P = A*P*A' + Q;
    K = P*H'/(H*P*H' + R);
    xhat = xhat + K*(x(n) - H*xhat);
    P = (eye(1) - K*H)*P;
    y(n) = xhat;
end

%% Plot time domain and frequency domain of original and filtered signal
t = 0:1/fs:length(x)/fs-1/fs;
subplot(2,1,1);
plot(t, x, 'b', t, y, 'r');
ylim([-1 1]);
legend('Noisy signal', 'Filtered signal');
xlabel('Time (s)');
ylabel('Amplitude');
title('Time domain plot');
subplot(2,1,2);
NFFT = 2^nextpow2(length(x));
f = fs/2*linspace(0,1,NFFT/2+1);
X = fft(x, NFFT)/length(x);
Y = fft(y, NFFT)/length(y);
plot(f, 2*abs(X(1:NFFT/2+1)), 'b', f, 2*abs(Y(1:NFFT/2+1)), 'r');
xlim([0 4000]);
legend('Noisy signal', 'Filtered signal');
xlabel('Frequency (Hz)');
ylabel('Magnitude');
title('Frequency domain plot');

需要注意的是，这只是一个简单的示例程序，实际情况下可能需要更复杂的处理方法和参数调整来获得更好的降噪效果。