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There are also different methods that have been proposed to fit a two-sided design for a given error spending function.
For a given error level, the suggested approach reduces the number of instantiations of the fields-level model compared to state-of-the-art methods.
Studies of the asymptotic behavior show that, for a given error tolerance, the new hybrid algorithm requires much less computer time than the stand-alone particle-mesh method (for this piloted-jet flame test case a factor of 20 times less).
DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit.
For a given error bound δ, P r(S t ≥δ) is higher when t is larger.
Clearly, in order to achieve the optimal profile for a given error rate, there must be some knowledge of the channel status even at the transmitter.
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Transmit diversity is necessary in harsh environments to reduce the required transmit power for achieving a given error performance at a certain transmission rate.
In order to summarize all the numerical results, a measure of the reliability of the prediction of the models is proposed: the mean absolute BER difference for a given code and a given error probability denoted as Γ l, p).
Furthermore, we show how to find an optimal sequence of simplification rules, such that their application yields a minimal model under a given error budget for performance estimation.
The coefficients must be chosen to minimize a given error metric for each angular interval delimited by the angles and.
This is reflected in Table 2, which shows the number of trips required on the binary tree to remain under a given error threshold for different parameter sets.
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