[人工智能]关于cnn的结构改进 并将分类西储大学的数据

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主要是先进行分析，然后--读取数据后 构造卷积网络模型

得到最后的结果

import torch
import numpy as np
import torch.nn as nn
import scipy.io as sio
from torch.utils.data import Dataset, DataLoader
from sklearn.preprocessing import maxabs_scale

class CWRU_DATA(Dataset):
    def __init__(self, data_num=100, data_len=1024):  # not overlapped
        self.data, self.label = self.prepare_data(num=data_num, length=data_len)  # (4, 100, 1024)

    def __len__(self):
        return len(self.label)

    def data_preprocess(self, x):
        x = x.astype(np.float32)  # shape: (N,)
        x = maxabs_scale(x)
        return x

    def prepare_data(self, num, length):
        NC = r"1./normal_0_97.mat"
        IF = r"1/12k_Drive_End_IR007_0_105.mat"
        OF 

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