5. In a magnetoencephalography (MEG) experiment, we attempt to partition the space of dipole model order versus reduced chi-square value for the dipole fit. This could be useful to an MEG researcher...

25. In a magnetoencephalography (MEG) experiment, we attempt to partition the space of dipole<br>model order versus reduced chi-square value for the dipole fit. This could be useful to an MEG<br>researcher in determining any trends in his or her data-fitting procedures. Typical ranges for<br>these parameters would be as follows:<br>Dipole model order (1, 2,.. ., 6)=X1i,<br>Reduced x2 E (1, 3)=x2i.<br>Suppose we have three MEG data points, Xi= (Xli, X2i), i= 1, 2, 3, to classify into two classes.<br>The data are<br>X1 = (2, 1.5), X2 = (3, 2.5) and x3 = (4, 2).<br>Find the optimum fuzzy 2-partition using the following initial partition:<br>U0) = 10 0<br>0 1 1<br>%3D<br>(Use m'= 2.0 and ɛL <0.01.)<br>

Extracted text: 5. In a magnetoencephalography (MEG) experiment, we attempt to partition the space of dipole model order versus reduced chi-square value for the dipole fit. This could be useful to an MEG researcher in determining any trends in his or her data-fitting procedures. Typical ranges for these parameters would be as follows: Dipole model order (1, 2,.. ., 6)=X1i, Reduced x2 E (1, 3)=x2i. Suppose we have three MEG data points, Xi= (Xli, X2i), i= 1, 2, 3, to classify into two classes. The data are X1 = (2, 1.5), X2 = (3, 2.5) and x3 = (4, 2). Find the optimum fuzzy 2-partition using the following initial partition: U0) = 10 0 0 1 1 %3D (Use m'= 2.0 and ɛL <>

Jun 06, 2022
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