To simulate Gaussian white random process.
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Stephen23
2020-10-15
To simulate Gaussian white random process.
Vinay Ahir on 1st of October 2020 at 15:02:
I have a system where the information arrival to the router of an IOT system is by a channel.
The arrival to this channel is according to a Gaussian white random process X(t) that is N(0, σ = 9) for 2 < t < 5, and 0 elsewhere. I need to simulate and plot 3 data sequences of such arrival, on the range t ∈ (0, 6).
Can you please help me?
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Ameer Hamza
2020-10-1
You can generate the noise vector like this
t = linspace(0, 6, 100); % 100 time samples between 0 and 5
x = zeros(size(t)); % noise vector
idx = 2 < t & t < 5;
x(idx) = randn(1, nnz(idx))*9; % N(0, sigma=9)
or If you have Statistical and Machine learning toolbox
x(idx) = normrnd(0, 9, 1, nnz(idx)); % N(0, sigma=9)
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