Sentence examples for matrix inverse c from inspiring English sources
This section describes the formulation of the recursive covariance matrix inverse C k - 1, and the calculation of E k based on C k - 1 - 1.
The recursive covariance matrix inverse C k - 1 is expressed in terms of a linear combination of weighted vectors, covariance matrix inversion of the previous channel C k - 1 - 1 (or weighted identity matrix inverse C 0 - 1 = 1 2 σ 2 I ( N + L - 1 ) for the first channel) and the allocated energy for the current channel E k.
Figure 12 Preliminary experiment: (a) Original scene; (b) optimal minimum norm matrix inverse; (c) 3D-LS solution; (d) matched-filter solution.
As the iterative calculation of energy Ek,i depends on C i − 1 − 1 which requires energies Ek, i−1) for k=1,…,K∗ for each iteration i, the SIC-based energy allocation method was developed to simplify the calculation of energy so that Ek,i depends only on Ek, i−1) and the stored covariance matrix inverse C k − 1 − 1 which is a function of E k − 1, I max.
where C ^ r is the consistent estimator of second-order CC given by (14), and Σ r is the asymptotic covariance matrix of C ^ r. (Σ r )− 1 and C ^ r T represent the matrix inverse of Σ r and transpose of C ^ r.
With MMSE relaying, we need to compute the inverse matrix of a N×N matrix to obtain ( g ̄, β ) for fixed ( B, C ̄ ) and the matrix inverse of a K×K matrix to obtain ( B, C ̄ ) for fixed ( g ̄, β ) in each iterative step.
If matrix A is ill-conditioned, its inverse C cannot be defined and the failure of finding the inverse indicates that the number of parameters is excessive.
Here, A T denotes the transpose of the matrix A, and (A T A −1 is the matrix inverse of A T A. Once best-fit values (x ¯ c, y ¯ c, α ¯ ) are obtained, the best fit curvature κ ¯ can be computed by its relation to z ¯ : κ ¯ = (α ¯ + x ¯ c 2 + y ¯ c 2 ) − 1.
The optimal minimum-norm matrix inverse and 3D-LS estimation are illustrated in Figure 12b, c, respectively, which can be compared to the standard matched-filter receiver in Figure 12d.
As a result, a linear equation solver which outputs C o v a r −1(p s )a can take over the places of the matrix inverse unit and the matrix multiplication unit.
