MATLAB: Hi. How can i add 20% Gaussian noise to some fixed value vector.

gaussain distributiongaussian white noise addition

Suppose i have a fixed value vector [1.05;0.2561;.3321]). I want to add 20% Gaussain noise to this vector such that this vector become the mean of the Gaussian distribution.

I hope that the question is clear

Thanks

Best Answer

   m = [ 1.05 ; 0.2561 ; 0.3321 ];
   s = 0.2 * m ;
   N = 1000;
   x =  ones(N,1) * m'  +  randn(N,3) * diag(s);

Related Solutions

MATLAB: How can i add 20% additive guassian noise to each and every element of vector

There is a function called randn() that you must have overlooked when you were searching for "random" in the help. Use that. It gives noise with zero mean and unit standard deviation so you'll have to scale it:

% Define our signal - a column vector.
a=[1.05;0.2561;.3321]
% Make the spread of the Gaussians be 20% of the a values
sigmas = 0.2 * a % Also a column vector.
% Create the noise values that we'll add to a.
randomNoise = randn(length(a), 1) .* sigmas
% Add noise to a to make an output column vector.
output = a + randomNoise

MATLAB: Adding noise with certain standard deviation to uncorrupted data

when you say 0.1047 rad/second, do you want these values to be bounded by a certain interval? or is the frequency value continuous (I'm assuming it is by rad/sec)

The other question is what probability distribution do you want the noise to follow and what is the mean value?

I'll assume here: Gaussian, mean 0, std 0.1047, frequency continuous

noise = 0.1047*randn(1000,1);  % gives you 1000 samples

Note you get negative and positive rad/second values -- that may very well not be what you want.

Best Answer

Related Solutions

MATLAB: How can i add 20% additive guassian noise to each and every element of vector

MATLAB: Adding noise with certain standard deviation to uncorrupted data

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