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The covaraince matrix is a crucial input in our analysis. In our analysis, we estimated the covaraiance matric from several off-source samples.
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We use the invesre of the covaraince matrix to compute the weigted inner product between two vectors, such as inner product between two templates or between template and on-source Y(\alpha). So, the accurate computatation of the inverse matrix is essential for getting the robust results. One can check this accuracy using the following property, the inverse of a matrix is such that if it is multiplied by the original matrix, it results in identity matrix. |
