How to reduce the color intensity of a noise signal?

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

Answer 1

[Yash]

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.