Ardo Illaste edited res_fitting2.md  almost 10 years ago

Commit id: 50081865ffac51c16ffe1a73240c0cf4782c3fac

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\[  \mathbf{r}_i = \left[\mathbf{p}_i,x_i,y_i\right]  =\left[A_i, d_i ,\tau_{d,i},\tau_{r,i},\mu_i,x_i,y_i\right] =  \left[\mathbf{p}^s_{i}, \mathbf{p}^p_{i}\right] \mathbf{p}^p_{i}\right],  \]  , where \(\mathbf{p}^s_i=\left[A_i,d_i,\tau_{d,i},\tau_{r,i}\right]\) is the shape parameter vector, \(\mathbf{p}^p_i=\left[\mu_i,x_i,y_i\right]\) is the position parameter vector and the whole parameter vector \(\mathbf{r}_i\) is obtained by combining the two. The *k*-th event detected in pixel *i* is represented by vectors   \(\mathbf{p}^s_{i,k}\) and \(\mathbf{p}^p_{i,k}\). These vectors can be stacked to create an event matrix (E) for pixel *i*: