[Eeglablist] EEG parameterization

Ibtissem KHOUAJA BENFRADJ ibtissem.khouaja at live.fr
Mon Jan 27 16:10:11 PST 2014


Thank you Tim so much for your answers, your support keeps me going 
andhelp me to better understand the needs of my work. 


I extrcted the matrix chains EEG from an (.edf) file, 
I want to find the linear equation that characterizes the dynamics of these signals as described in the article:
 "A MATLAB toolbox for Granger causal connectivity analysis",

x1(t) = 0.95 √2x1(t − 1) − 0.9025x1(t − 2) + w1(t)
x2(t) = 0.5x1(t − 2) + w2(t)
x3(t) = −0.4x1(t − 3) + w3(t)
x4(t) = −0.5x1(t − 2) + 0.25√2x4(t − 1) + 0.25√2x5(t − 1)+w4(t)
x5(t) = −0.25√2x4(t − 1) + 0.25√2x5(t − 1) +w5(t)

how these factors can be extracted?

thanks in advance,

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



From: mullen.tim at gmail.com
Date: Wed, 15 Jan 2014 18:26:48 -0800
Subject: Re: [Eeglablist] EEG parameterization
To: ibtissem.khouaja at live.fr
CC: eeglablist at sccn.ucsd.edu

The function (<sift-root>/est/est_fitMVAR_DEKF.m) is included in SIFT 1.0-beta and later, which you can obtain from the EEGLAB plugin manager or the SIFT website.
Best,Tim



On Wed, Jan 15, 2014 at 5:28 AM, Ibtissem KHOUAJA BENFRADJ <ibtissem.khouaja at live.fr> wrote:






Thank you Tim,
I actually need the non linear filter to study the EEG signaland to extract these features.

I find the linear filte (est_fitMVARKalman) on the net but I can't find the socond one (est_fitMVAREKF).


Can you send me the link.

thanks a lot.
-----------
Ibtissem KHOUAJA BENFRADJ

PhD in computer scienceSpeciality Signal ProcessingLaboratory LTIM, University of Monastir, Tunisia

http://www.labtim.org/accueil.phpLaboratory LIGM, Univerisity of Paris-East, France 

http://ligm.u-pem.fr/





> Date: Wed, 8 Jan 2014 18:04:46 -0800
> Subject: Re: [Eeglablist] EEG parameterization
> From: mullen.tim at gmail.com


> To: ibtissem.khouaja at live.fr; eeglablist at sccn.ucsd.edu
> CC: 


> 
> There are linear and nonlinear kalman filter-based multivariate autoregressive implementations in the Source Information Flow Toolbox for EEGLAB. See est_fitMVARKalman and est_fitMVARDEKF. 
> 
> Tim


> 
> -----Original Message-----
> Date: Wednesday, January 08, 2014 1:40:42 pm
> To: "EEGLAB-list" <eeglablist at sccn.ucsd.edu>


> From: "Ibtissem KHOUAJA BENFRADJ" <ibtissem.khouaja at live.fr>
> Subject: Re: [Eeglablist] EEG parameterization
> 
> 

> 

> 
> 
> Thank you very much for your answers and happy new year 2014.
> On my first question, I am based on your set and literature and I will present the EEG signal from a set of evolutionary parameters based on the Kalman filter.


> This gives the possibility of reconstructing the signal and to predict its evolution.
> Is there someone who work with this type of auto-regressive filter?I need the algorithm in Matlab.
> Thank a lot for your precious help, Ibtissem


> 
> 
> 
> ---------------------------------------------------------------------------
> ---------------------------------------------------------------------------
> > From: poil.simonshlomo at gmail.com


> > Date: Thu, 19 Dec 2013 21:43:51 +0100
> > Subject: Re: [Eeglablist] EEG parameterization
> > To: ibtissem.khouaja at live.fr
> > CC: eeglablist at sccn.ucsd.edu


> > 
> > Dear Ibtissem,
> > 
> > There are several ways you can characterize an EEG signal. The two
> > basic are frequency and amplitude in different frequency bands (and
> > spatial location). You can see more here:


> 
 		 	   		  


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