a data.mat as the cnn-resnet18' input and a clean data.mat as its output in matlab in matlab

main.m
% Load the data
load('data.mat');
load('clean_data.mat');

% Define the ResNet-18 network 
net = resnet18;

% Convert the data into single precision
data = single(data);

% Normalize the data
data = bsxfun(@minus, data, net.Layers(1).Mean);
data = bsxfun(@rdivide, data, net.Layers(1).StandardDeviation);

% Feed the data to the ResNet generator
predicted_clean_data = predict(net, data);

% Compare the predicted data with the actual "clean" data
% and display the mean squared error (MSE)
mse = immse(predicted_clean_data, clean_data);
fprintf('Mean Squared Error: %f\n', mse);
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