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Moreover, the cross-boundary coverage problem can be estimated by considering the distance of the test point of section having problems and the site location of serving cell.
If complete structural information is taken as 100% then the fraction of complete structural information q extracted from spectra as a result of the solution of the problem can be estimated by the ratio.
It is well known (see e.g. [9,10]) that in the case of semi-Lagrangian methods the error of the fully discretized problem can be estimated by (2) ‖ u (n τ, x ) − u n (x ) ‖ ≤ C (h q + h q τ ), where h is the grid size, and q is the order of the space discretization (for example, the order of the Lagrange interpolation).
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Then, 2D DOA can be estimated by solving two 1D DOA estimation problems successively instead of directly estimating 2D DOA.
For reliability problems entailing multiple design points, failure probability can be estimated by the multi-point first-order reliability method (FORM), which gives the probability of the union of approximate events.
In this way, the mixing matrix A can be estimated by solving the following problem.
The distribution can be estimated by formulating a maximum likelihood problem [30, 31], where the parameters in a family of distributions are optimized to fit the data.
The WCET can be estimated by solving the maximum cost circulation problem of the set of constraints that describes program behavior.
On the other hand, the impulsive instants can be estimated by solving a sequence of maximum value problems when the impulsive gains and some parameters are fixed.
For any given toll-charge pattern, its impact on the mode-split can be estimated by solving a combined mode-split and traffic-assignment problem.
The mean vector, bases, and the corresponding projections can be estimated by maximizing the data likelihood which is an optimization problem equivalent to minimizing (1).
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