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One algorithm determines the optimal time delay in the reference model by solving an optimization problem, whereas the other algorithm avoids the nonlinear optimization by using a simple approximation for the time delay term, enabling derivation of analytical PID tuning formulas.
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For the boundary layer analysis of Section 2 we use a simple approximation for Φ S that is independent of y.
We will use a simple approximation of these dependencies as dependence on the mean expression μ = (μ1 + μ2)/2 only.
Based on analytical simulation using a simple parallel-plate approximation, scaling guideline is derived in terms of pull-in, release voltage, pull-in time and release time.
The proposed models were then proved to be useful for predicting pyrolysis behavior in real biomass and so could be used as a simple approximation for predicting the overall trend of chemical reaction kinetics.
However, we note that expected delay analysis, similar to the one presented in Table 2, could be used as a simple approximation for the layer-by-layer decode-and-broadcast system design.
However, as a first approximation, using a simple, linear extrapolation, we showed that, in the specific case of the Coelomata-Ecdysozoa dilemma, taking into account parallel changes does not affect the support for Coelomata but eliminates much of the support for Ecdysozoa.
Based on this approximation, these moments are estimated using a simple covariance fitting optimization technique.
An unwitting approximation to the tropical year may also be obtained by intercalation, using a simple lunar calendar and observations of animal behaviour.
The estimation of the matrix influence enables the approximation of the position of a priori unknown responsivity and was easily evaluated using a simple algorithm.
Therefore, most systems use a simple Viterbi approximation that measures the goodness of a string using only its most probable derivation.
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