Hi,
To represent the noise “n”, given that it occurs with a probability of 4%, you can use a combination of random number generation and conditional logic. For probability check you can use the “rand()” function to generate a random number between 0 and 1, If this number is less than 0.04, you introduce noise. Refer to the example code below:
% Define the probability of noise occurrence
probability_of_noise = 0.04;
% Define the range or standard deviation of the noise if it occurs
noise_magnitude = 1; % You can adjust this as needed
% Generate a random number to decide if noise occurs
if rand() < probability_of_noise
% If noise occurs, generate noise
n = noise_magnitude * randn(); % Gaussian noise
else
% If noise does not occur, set n to zero
n = 0;
end
% Example usage with a given input x
x = 10; % Example input
y = x + n; % Calculate the output
For noise generation, I have used the “randn()” function which generates a random number from a standard normal distribution. You can scale this by a noise magnitude to adjust the level of noise.
For more information on the “rand” and “randn” functions refer to the below documentations:
