Hi,
To decrease the color intensity of the noise before adding it to the PD signal, you can adopt one of the following approaches:
Method-1:
Multiply the noise by a factor less than 1. This will reduce the amplitude of the noise and make it less prominent in the combined signal.
% Decrease the color intensity of the noise
intensity_factor = 0.5; % Adjust this factor as needed
Reduced_Noise = intensity_factor * Normal_Noise;
By multiplying the Normal_Noise by the intensity_factor, the amplitude of the noise is scaled down before adding it to the PD signal. You can adjust this factor to achieve the desired level of reduction.
Method-2:
Another approach is to apply a filter to the noise to make it less sharp. A simple averaging filter can be used to smooth out the noise, which can make it appear less intense when visualized.
% Apply a filter to the noise to smooth it out
filter_size = 3; % Adjust this size as needed
filter_kernel = ones(filter_size) / (filter_size ^ 2);
Smoothed_Noise = conv2(Normal_Noise, filter_kernel, 'same');
Please adjust the scaling_factor or filter_size according to your specific requirements and test the results to see if they meet your needs for pattern recognition accuracy with CNN.
