the clean seismic data which is 1*2500 were taken as the training labels of the resnet18 in matlab

To clean seismic data, you can follow the following steps in MATLAB:

  1. Load the seismic data using load command.

  2. Preprocess the data by detrending and removing the mean.

  3. Apply a bandpass filter to remove the unwanted frequencies.

  4. Apply noise reduction techniques like wavelet denoising or empirical wavelet transform.

  5. Normalize the data to a range of 0 to 1.

Here's an example code snippet to get you started:

main.m
% Load data
data = load('seismic_data.mat');
seismic_data = data.seismic_data;

% Preprocessing
seismic_data = detrend(seismic_data);
seismic_data = seismic_data - mean(seismic_data);

% Bandpass filter
fs = 2500; % Sampling frequency
f1 = 1;    % Lower cutoff frequency
f2 = 50;   % Upper cutoff frequency
[b, a] = butter(4, [f1, f2]/(fs/2), 'bandpass');
seismic_data_filt = filtfilt(b, a, seismic_data);

% Noise reduction
seismic_data_denoised = wdenoise(seismic_data_filt);

% Normalization
seismic_data_clean = normalize(seismic_data_denoised);
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Once you have cleaned the data, you can use it as the training labels for ResNet18.

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