[Eeglablist] Eigenvalues generation

[Ibtissem KHOUAJA BENFRADJ]

Hi Matt, 
I thank you so much for your reply.

Really, you have undersatand very well my goal. 
In fact, I'd like to know if you have applied a specific algorithm for the generation of the AR matrix (A). 
In my work, I applied the algorithm 'arfit', and it gives me a vector  of p AR parameters for each signal.

In this case, how can I present my matrix to extract the eigenvalues?

Thank's a lot for your reply, Ibtissem

--------------------------------------------------------------------------------------------------------------------Ibtissem KHOUAJA BENFRADJPhD in computer scienceSpeciality: Biomedical Signal ProcessingLaboratory: LTIM, University of Monastir, Tunisiahttp://www.labtim.org/accueil.phpLaboratory: LIGM, Univerisity of Paris-East, France http://ligm.u-pem.fr/



Date: Tue, 3 May 2016 21:09:01 +0200
Subject: Re: [Eeglablist] Eigenvalues generation
From: matt.gerhold at gmail.com
To: ibtissem.khouaja at live.fr
CC: eeglablist at sccn.ucsd.edu

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 BENFRADJPhD in computer scienceSpeciality: Biomedical Signal ProcessingLaboratory: LTIM, University of Monastir, Tunisiahttp://www.labtim.org/accueil.phpLaboratory: LIGM, Univerisity of Paris-East, France http://ligm.u-pem.fr/

 		 	   		  

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