Sentence examples for a probability when from inspiring English sources

The long run probability measures of the different states of the system like probability of the system being in accumulation state P(A), probability when the first permanent repairman is in busy state P FB) and the probability when both repairmen are in busy state P BB) have also been explored numerically for the variation in different parameters.

Furthermore, rejection of a merger has a higher probability when the CW standard (a tougher criterion) is applied.

Since the hypothesis being pruned generally has a very small a posteriori probability when compared with the ones that are not being pruned, we believe this effect could be ignored.

For instance, we demand a higher probability when the cost of accepting a false hypothesis is high.

Using a simple optimization technique, DRED randomly discards packets with a load-dependent probability when a buffer in a router gets congested.

The cumulative binomial test was used to examine the likelihood that the occurrence of a particular event (loss of the same allele in the invasive carcinoma and an associated epithelial sample) occurs at a particular probability when observed in repeated trials.

Under a certain probability, when is less than 0, such a value is rounded to 0 in order to avoid the underflow.

According to the results of this study, an error greater than 5 bpm will occur with a 5% probability when the pulse is counted for 15 s and multiplied by 4. Therefore, when a value of 70 bpm is obtained for a 15 s measurement, the 95% confidence interval is estimated to be 65 75 bpm.

The event 'the side-length lies in [0, 1/2]', receives a different probability when merely redescribed.

It was also discussed in Section 4 that the resulting Θtot(t)=Ψtot(t)ϕ satisfies the RIP condition with a high probability, when the local network coding coefficients are generated according to the assumptions of Theorem 1, with a number of measurements m of the same order as would be required for a i.i.d.i.d

Using the results above, it can be understood that an m×n i.i.d Gaussian random matrix, G, satisfies RIP of order k, with a high probability, when the order of number of measurements, m, is k log(n/k), formally writing: m = O k log n k, (24).