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The BMI condition can be solved by using BMI solvers.
The design condition can be solved easily by efficient convex optimization algorithms.
The condition can be solved by means of linear matrix inequality relaxations with slack variables and Lyapunov matrices which are considered as homogeneous polynomials of arbitrary degree.
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The conditions can be solved by linear programming.
All present conditions can be solved by linear programming.
(36)–(40) with boundary and initial conditions can be solved efficiently by the finite difference method.
Now Eq. (10) along with initial and boundary conditions can be solved using perturbation method.
The analysis reveals that the conditions can be solved by using block Gauss-Seidel (GS) schemes.
(4a) and (4b) without constraint conditions can be solved by the Levenberg Marquardt method, an iterative method.
We show that checking such necessary and sufficient conditions can be solved with a complexity that is combinatorial with respect to the number of input and output signals.
and the junction conditions at z = L/2 yield for n ≥ 0 from the continuity of E r, and from the continuity of D z, These conditions can be solved through.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com