用python写平稳噪声估计算法

以下是使用Python实现平稳噪声估计算法的示例代码：

import numpy as np
from scipy.signal import lfilter

def stationary_noise_estimate(signal, block_size):
    # Split the signal into overlapping blocks
    num_blocks = signal.size // block_size
    blocks = np.zeros((num_blocks, block_size))
    for i in range(num_blocks):
        blocks[i,:] = signal[i*block_size:(i+1)*block_size]
    
    # Compute the autocorrelation matrix for each block
    r = np.zeros((block_size, block_size))
    for i in range(num_blocks):
        r += np.outer(blocks[i,:], blocks[i,:])
    r /= num_blocks
    
    # Compute the eigenvectors and eigenvalues of the autocorrelation matrix
    eigvals, eigvecs = np.linalg.eig(r)
    
    # Sort the eigenvalues in descending order
    idx = np.argsort(eigvals)[::-1]
    eigvals = eigvals[idx]
    eigvecs = eigvecs[:,idx]
    
    # Compute the noise subspace
    noise_subspace = eigvecs[:,eigvals < np.mean(eigvals)]
    
    # Compute the noise estimate by projecting the signal onto the noise subspace
    noise_est = np.zeros_like(signal)
    for i in range(num_blocks):
        block = blocks[i,:]
        projection = np.dot(noise_subspace, block)
        noise_est[i*block_size:(i+1)*block_size] = np.dot(noise_subspace.T, projection)
    
    # Apply a smoothing filter to the noise estimate
    smoothing_filter = np.ones(10) / 10
    noise_est = lfilter(smoothing_filter, 1, noise_est)
    
    return noise_est

该示例代码中的主要函数是`stationary_noise_estimate`，它接收两个参数：`signal`为要估计噪声的信号，`block_size`为用于估计噪声的块大小。该函数将信号分割成重叠的块，并计算每个块的自相关矩阵。然后，它计算自相关矩阵的特征向量和特征值，并将它们按降序排序。使用特征值小于平均特征值的特征向量来构建噪声子空间，并将信号投影到噪声子空间上以估计噪声信号。最后，它应用一个平滑滤波器来平滑噪声估计。

要使用该函数，可以从文件中读取音频信号，并将其传递给`stationary_noise_estimate`函数：

import soundfile as sf

# Load audio signal
signal, samplerate = sf.read('signal.wav')

# Estimate stationary noise
noise_est = stationary_noise_estimate(signal, block_size=2048)

# Subtract noise from signal
clean_signal = signal - noise_est

# Write cleaned signal to file
sf.write('clean_signal.wav', clean_signal, samplerate)

该示例代码将从名为`signal.wav`的文件中读取音频信号，并使用块大小为2048来估计噪声。它将估计出的噪声从原始信号中减去，并将结果写入名为`clean_signal.wav`的文件中。