<div dir="ltr">Dear Ibtissem,<div><br></div>> knowing that the EEG signal is a non-periodic and non-stationary signal, how can we apply there the Kalman filter?<br><br>The stationarity of EEG signal depends on the length of time window; longer, more non-stationary (in principle). For example, in 24 hours you sleep, wake up, work, rest... in 24 minutes, you maybe doing a single job constantly... in 24 seconds you are in the middle of something... in 240 milliseconds your brain may be processing only a few ongoing events.<div><br></div><div>> From the AR matrix, how can we regain the starting signal (I used 'filter' function under matlab but it does not give the desired result)?<br><br>I don't understand the question. I'm not qualified to answer it either anyways.<br><br>> Finally, do you have an idea about the decomposition of the EEG signal in Fourier series?<div class="gmail_extra"><br></div><div class="gmail_extra">You mean something other than the coefficients of the Fourier series? :-)</div><div class="gmail_extra"><br></div><div class="gmail_extra">Makoto</div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Mar 17, 2015 at 4:23 PM, Ibtissem KHOUAJA BENFRADJ <span dir="ltr"><<a href="mailto:ibtissem.khouaja@live.fr" target="_blank">ibtissem.khouaja@live.fr</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
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<div dir="ltr"><font face="Times New Roman,sans-serif" color="#000000"><br></font><font style="font-size:12pt" size="3"><font face="Arial, sans-serif">Dear list,</font></font><br><div><font face="Arial, sans-serif" size="3"> </font></div><div><font face="Arial, sans-serif" size="3">I need your help to overcome some problems that I met.</font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">I read the article<i> "Kalman filter parameters </i></font><i style="font-family:Arial,sans-serif;font-size:medium">as a new feature vector for EEG BCI applications."</i><span style="font-family:Arial,sans-serif;font-size:12pt"> (Amir Omidvarnia)<br></span></div><div><font face="Arial, sans-serif" size="3">I also tested the algorithm DEKF on Matlab on a portion of the EEG signal</font></div><div><font face="Arial, sans-serif" size="3">(100 points, order 10) to generate the autoregressive matrix. </font></div><div><font style="font-size:12pt" face="Arial, sans-serif" size="3">As a resulted, I have got a matrix [1 * 10] for each cahnnel.<br></font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">My questions are:</font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">knowing that the EEG signal is a non-periodic and non-stationary signal, </font></div><div><font face="Arial, sans-serif" size="3">how can we apply there the Kalman filter?</font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">From the </font><span style="font-family:Arial,sans-serif;font-size:12pt">AR</span><span style="font-family:Arial,sans-serif;font-size:12pt"> </span><span style="font-family:Arial,sans-serif;font-size:12pt">matrix, how can we regain the starting signal (I used </span><span style="font-family:Arial,sans-serif"> 'filter'</span><span style="font-family:Arial,sans-serif;font-size:12pt"> function under matlab but it does not give the desired result)?</span></div><div><span style="font-family:Arial,sans-serif;font-size:12pt"><br></span></div><div><font face="Arial, sans-serif" size="3">Finally, do you have an idea about the decomposition of the EEG signal in Fourier series?</font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">Thank you in advance for your answers.</font></div><div><font face="Arial, sans-serif" size="3"><br></font></div><div><font face="Arial, sans-serif" size="3">cordially,</font></div><br><div><font style="background-color:rgb(255,255,255)" face="Comic Sans MS" color="#666666">----------------------------------------------------------</font></div><div><font style="background-color:rgb(255,255,255)" face="Comic Sans MS" color="#666666">----------------------------------------------------------</font></div><font style="background-color:rgb(255,255,255)" face="Comic Sans MS" color="#666666">Ibtissem KHOUAJA BENFRADJ</font><div><span style="background-color:rgb(255,255,255)"><font face="Comic Sans MS" color="#666666">PhD in computer science</font></span></div><div><span style="background-color:rgb(255,255,255)"><font face="Comic Sans MS" color="#666666">Speciality Signal Processing</font></span></div><div><span style="background-color:rgb(255,255,255)"><font face="Comic Sans MS" color="#666666">Laboratory LTIM, University of Monastir, Tunisia</font></span></div><div><a href="http://www.labtim.org/accueil.php" target="_blank"><font style="background-color:rgb(255,255,255)" face="Comic Sans MS" color="#666666">http://www.labtim.org/accueil.php</font></a></div><div><span style="background-color:rgb(255,255,255)"><font face="Comic Sans MS" color="#666666">Laboratory LIGM, Univerisity of Paris-East, France </font></span></div><div><a href="http://ligm.u-pem.fr/" target="_blank"><font style="background-color:rgb(255,255,255)" face="Comic Sans MS" color="#666666">http://ligm.u-pem.fr/</font></a></div><div><span style="background-color:rgb(255,255,255)"><font face="Comic Sans MS" color="#666666"><br></font></span></div><div><span style="font-size:12pt"><br></span></div> </div></div> </div></div>
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