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If simplified AF schemes are used, where only power allocation is done, G and J are diagonal matrices, the coefficients of which can be designed as a function of the mean channel and noise powers [5] or optimized from power allocation strategies, as shown recently in [22].
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On the contrary, at the edges of the matrix, the coefficients are significantly different.
In the anti-image correlation matrix the coefficients were well above the accepted level of 0.5.
For matrices where the coefficients are well conditioned.
After the relationship between the transfer matrix and the coefficient matrix is established, the fourth order Runge Kutta method is used numerically to solve the matrix equation.
The matrix comprises the coefficients (3).
Previous results on robust stability of Metzlerian matrices are extended to matrix polynomials, with the coefficient matrices having exactly the same Metzlerian structure.
The input of the algorithm are the matrix coefficients of the power series expansion of the perturbed matrix.
The matrixes contain the coefficient estimates (R2 values) for a multilinear regression of the brain-to-brain entrainment response using as predictors the brain entrainment to speech of the listeners and the speakers.
Under the regression matrix P∈ℜ d × c 2, the least squares loss is defined by (7) where X is the data points matrix, P is the coefficient matrix of regression with c2 tasks, the label matrix.
The matrix Q is the coefficient matrix in the mixed model equations and the inverse of this matrix is where.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com