How to generate Gaussian white noise with certain variance in Matlab?

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Hey, I have a signal Xmodt to which I want to add Gaussian white noise W with mean value equal to zero (by definition) and variance equal to 1/(Ts*(10^(SNRdb/10))). From what I have found online, I created the following code:
Ts=0.1; %Given sampling period
SNRdb = 10; %Given SNRdb
variance = 1/(Ts*(10^(SNRdb/10)));
W = sqrt(variance).*randn(1,size(Xmodt,2)); %Gaussian white noise W
Xmodt = Xmodt + W; %Add the noise
I know that in this example variance equals to 1, but I need to find a general solution. So, is this code correct? Thanks in advance!

Risposta accettata

Walter Roberson
Walter Roberson il 7 Dic 2013
Skip the first 2 lines, assign the desired value to the variance, and continue on with W and Xmodt.
  1 Commento
Konstantinos
Konstantinos il 8 Dic 2013
Modificato: Konstantinos il 8 Dic 2013
Well, the first 3 lines are not my problem but I added them for typical reasons. So, you mean that the last 2 lines of code are correct? Do they produce and add white Gaussian noise to the signal?

Accedi per commentare.

Più risposte (3)

Zerihun Abebe
Zerihun Abebe il 26 Apr 2016
Computer Experiment. Consider the linear system defined by Generate 1500 samples of a unit-variance, zero-mean, white-noise sequence xn, n = 0, 1, . . . , 1499 and filter them through the filter H to obtain the output sequence yn. Compute the sample cross-correlation ˆRyx(k) for k = 0, 1, . . . , 50 to obtain estimates of the impulse response hk. On the same graph, plot the estimated impulse response versus time, together with the simulated response Repeat, using a different realization of xn.

fluid
fluid il 22 Ott 2017
Modificato: fluid il 22 Ott 2017
y1 = wgn(1000, 1, 0); % a 1000-element white noise with power 0dBW, that is 1W
var(y1)
ans:
ans = 0.9979

Juan José Retana Díaz
Juan José Retana Díaz il 27 Ott 2022
I have a doubt, what does the number "2" means in the line: W = sqrt(variance).*randn(1,size(Xmodt,2));
Please help me, I need to add white gaussian noise to a signal with zero mean and a variance of 4.7 x 10^-5.

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