I am new to MATLAB and I am trying to built a voice morphing system using MATLAB.
So I would like to know how to normalize a signal to zero mean and unit variance using MATLAB?
This question is related to
matlab
signal-processing
It seems like you are essentially looking into computing the z-score or standard score of your data, which is calculated through the formula: z = (x-mean(x))/std(x)
This should work:
%% Original data (Normal with mean 1 and standard deviation 2)
x = 1 + 2*randn(100,1);
mean(x)
var(x)
std(x)
%% Normalized data with mean 0 and variance 1
z = (x-mean(x))/std(x);
mean(z)
var(z)
std(z)
If you have the stats toolbox, then you can compute
Z = zscore(S);
You can determine the mean of the signal, and just subtract that value from all the entries. That will give you a zero mean result.
To get unit variance, determine the standard deviation of the signal, and divide all entries by that value.
To avoid division by zero!
function x = normalize(x, eps)
% Normalize vector `x` (zero mean, unit variance)
% default values
if (~exist('eps', 'var'))
eps = 1e-6;
end
mu = mean(x(:));
sigma = std(x(:));
if sigma < eps
sigma = 1;
end
x = (x - mu) / sigma;
end
Source: Stackoverflow.com