"Lars Hansen" <invalid@nospam.com> wrote in message
news:43428bfc$0$78287$157c6196@dreader1.cybercity.dk...
> whitening of a time series changes the power spectrum of the time series
> such that it is flat (in theory) and any two samples of the whitened time
> series are uncorrelated.
>
>
>
If the original time-series can be modelled as white noise passing through a
stable filter F(z) then by passing the time series through 1/F(z) we get
back to a white noise sequence.
This is more complicated if we have the same as above and then have additive
uncorrelated noise (white or otherwise).Then we get a spectral factor as the
colouring transfer function instead of F(z) but the basic idea is the
same.ie suppose u(k) is white and is uncorrleated with v(k) - anotehr white
noise sequence.
Then
y(k)=F(z)u(k) +v(k)
wnd the spectrum of y is
phiyy(z) = FF* X power of u + power of v
where * denotes conjugate. We can then factorise the power spectrum]
phiyy(z)= EE* where E is the spectral factor and the colouring transfer
function in fact.
If we use 1/E as a whitening filter for y(k) we arrive at a third white
noise sequence called the innovations.
McC
Reply by Henrietta Denoue●October 4, 20052005-10-04
Lars Hansen wrote:
> whitening of a time series changes the power spectrum of the time series
> such that it is flat (in theory) and any two samples of the whitened time
> series are uncorrelated.
>
>
>
Thanks Lars for the answer.
But why would I want to lose correlation information ?
H.
Reply by Lars Hansen●October 4, 20052005-10-04
whitening of a time series changes the power spectrum of the time series
such that it is flat (in theory) and any two samples of the whitened time
series are uncorrelated.
Reply by Henrietta Denoue●October 4, 20052005-10-04
Could someone please explaing to me what prewhitening
of a time series does ? Or prewhitening the autocorrelation
and finding the minimum phase signal from this ?
Thanks
H.