Since it is a diagonal matrix, the inverse matrix (mathbf {S}_{i}^{-1}) is readily derived by taking the reciprocal of each element, which costs q divisions.
Here we study the calculation of the Fisher information matrix, the inverse of the Cramer Rao lower bound, from a system theoretic point of view.
The upstream system, since it usually has much larger capacity than the LV grid, can be simplified by Thevenin equivalent, where a method to obtain the impedance is Z-bus matrix, the inverse matrix of the admittance matrix.
First, we show formal errors, i.e., the square root of the diagonal components of the covariance matrix, the inverse of the normal matrix, which is related to the non-uniform distribution of the accuracy of the tomography results.
Thus, the inverse of the NRM is calculated by the products of the lower triangular matrix that identifies the parents of each individual, its transpose matrix, the inverse of the K matrix and the inverse of diagonal matrix D, in which the diagonal elements comprise a number of known parents and their inbreeding coefficients.
In case of the value-weighted matrix, the inverse class probabilities of the values are mapped to the compounds that represent the corresponding value and class.
For some measures described below however, we either considered the network as unweighted (each node either connected or not) or as a similarity matrix (the inverse of the distances measures).
For matrix T, the inverse matrix T-1 is a lower triangular matrix with diagonal elements equal to 1 and in the lower diagonal, the only non-zero elements are -0.5 for offspring parent elements.
The measurement matrix (varPhi _t) is formed by a subset of k vectors selected from the projection matrix (varPhi ), which in our case is constructed by the DFT matrix and the inverse DWT matrix.
The matching model matrices and the inverse filters are given in (7) and (8).
