小波去噪pytorch代码实现

以下是使用PyTorch实现小波去噪的代码示例：

import torch
import pywt

# 定义小波去噪模型
class WaveletDenoising(torch.nn.Module):
    def __init__(self, wavelet='db4', level=1):
        super(WaveletDenoising, self).__init__()
        self.wavelet = wavelet
        self.level = level

    def forward(self, x):
        # 小波分解
        coeffs = pywt.wavedec(x, self.wavelet, level=self.level)
        # 对每个细节系数进行阈值处理
        thresholded_coeffs = [pywt.threshold(c, value=0.5*max(c)) for c in coeffs]
        # 小波重构
        denoised_x = pywt.waverec(thresholded_coeffs, self.wavelet)
        return denoised_x

# 创建小波去噪模型实例
model = WaveletDenoising()

# 加载待去噪的数据
data = torch.tensor([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], dtype=torch.float32)

# 进行小波去噪
denoised_data = model(data)

# 打印去噪后的数据
print("Denoised data:", denoised_data)