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How to reduce the color intensity of a noise signal?

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I have two signals, one is PD signal (40*600) and other is noise (40*600), Now both are added
sd=0.005;
Normal_Noise= sd*abs(randn(size(cQFTs))); % cQFTs is PD signal of 40*600;
cQFTs=cQFTs+Normal_Noise;
the pattern shows cQFTs with thin color and Noise with thick color, this effects my pattern recognition accuracy with CNN. How can I decrease the color intensity of Noise before adding to the PD signal?
A file is attached which contains PD signal (scattered on the plot) and Noise (at X axis) for reference

Answers (1)

Yash
Yash on 20 Feb 2024
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.

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