[Eeglablist] Eigenvalues generation

[Matt Gerhold]

Hi,

One would compute the eigenvalues for the autoregressive parameter
matrix--your estimated beta coefficients. This would be to assess the
stability of the system. One only needs to compute these eigenvalues for
this matrix; nothing more nothing less... Then take the modulus of the
eigenvalues, they should all be less than one. Following Lutkepohl (2005),
a simple way to do this is:

if A = autoregressive parameters (K x K), where K is number of
data-channels:

>> eig_vals = abs(diag(jordan(A))) % jordan canonical form of A
>> eig_vals < 1 % should give a vector of 1's if the system is stable

Regards,

Matthew


On Mon, May 2, 2016 at 6:20 PM, Ibtissem KHOUAJA BENFRADJ <
ibtissem.khouaja at live.fr> wrote:

> Dear list,
>
>
> I applied the ARFIT algorithm in the generation of autoregressive
> parameters
> corresponding to the time-varying of EEG.
> Nest, in order to generate the eigenvalues of the AR matrix I used ARMODE
> algorithm.
>
> I need your help to generate differently the eigenvalues for the AR
> parameters of each signal (AR vector) and all of signal (AR matrix).
>
> Thank you for your help, Ibtissem
>
> ----------------------------------------------------------
> ----------------------------------------------------------
> Ibtissem KHOUAJA BENFRADJ
> PhD in computer science
> Speciality: Biomedical Signal Processing
> Laboratory: LTIM, University of Monastir, Tunisia
> http://www.labtim.org/accueil.php
> Laboratory: LIGM, Univerisity of Paris-East, France
> http://ligm.u-pem.fr/
>
>
>
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