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Results obtained from the simulation approach show that for relatively large networks, the maximum absolute relative error between the simulation and the actual M2TR is less than 0.9%, yet when considering approximation formulae, this error can be as large as 18.97%.
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Strategies for the suppression of plate vibration are investigated by considering approximations to the equivalent impedance of power-minimizing vibration controllers.
Considering approximations employed, it is surprising that the calculated C8-50 concentrequiredequired to form a monolayer (2 μg/mL) is within a factor of 2 of the MIC, 4.0 (±1.2) μg/mL for E. coli.
Consequently, it is of interest to consider approximation methods that may lead to more stable covariance matrix estimators.
Moreover, for convenience, we may assume that the appropriate weak solution is smooth, and no longer consider approximation problem.
We consider approximation of X by piecewise Hermite interpolation splines with n free knots (i.e., a sampling design, a mesh).
Limitations of the model concern the considered approximation of the camera model, affine instead of fully perspective, but, experimentally, it has been shown not to be very limiting.
In this survey we consider approximation and online algorithms for several classical generalizations of bin packing problem such as geometric bin packing, vector bin packing and various other related problems.
Note that the numerical results reported in the next section show that the considered approximation of (25) leads to a symbol timing estimator with satisfactory performance if the number of subcarriers is sufficiently large.
For this approach, we refer to the book of Gal [1], where he considers approximation properties of several complex operators such as Bernstein, q-Bernstein, Favard-Szasz-Mirakjan, Baskakov and some others.
In this paper, we consider approximation of the population likelihood by using the first-order conditional estimation with interaction (FOCEI) approximation of the population likelihood together with the EKF for state estimation on the individual level.
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