Whitening filter We will now use a whitening filter to whiten a data stream. The test data for this you will find in your data packet in 'topic2'. We start by loading the xml file:
>> a = ao('topic2/white.xml');

a is now an AO containing coloured noise. Let's have a look at this times series using iplot.

>> iplot(a);
coloured

We have to define the parameter list for the whitening tool:

>> pl = plist(...
    'model', [], ...
    'MaxIter', 30, ...
    'PoleType', 1, ...
    'MinOrder', 2, ...
    'MaxOrder', 9, ...
    'Weights', 2, ...
    'Plot', false,...
    'Disp', false,...
    'RMSEVar', 5,...
    'FitTolerance', 0.6); % tolerance on fit residuals spectral flatness

No we can call the whitening function 'whiten1D' with our AO, a and the parameter list pl:

 >> aw = whiten1D(a,pl); 

To compare the whitened data with the coloured noise we compute the power spectrum (details see Power spectral density estimation):

>> awxx = aw.psd;
>> axx   = a.psd;

and finally plot our result in the frequency domain:
The whitened data (awxx) compared to the coloured noise that was our input (axx).

>> iplot(axx, awxx);
white