Sentence examples for probability requirements from inspiring English sources

To efficiently extend the WSNs lifetime with users' pre-defined failure probability requirements, only the sensors from the current active sensor cover are responsible for monitoring all targets, while all other sensors are in a low-energy sleep mode.

The method consists of a sequence of classical designs, based on given safety factors, that (a) minimize cost or optimize an alternative objective function, (b) calculate the different failure mode probabilities or their upper bounds, and (c) update the safety factors to satisfy both the safety factors and the failure probability requirements.

Numerical results illustrate that as the intercept probability requirement loosens, the outage probability of proposed multiuser scheduling scheme decreases accordingly, showing the trade-off between security and reliability.

Further, the logic is investigated for safety critical application in a nuclear power plant with a very low unsafe failure probability requirement.

In [12], PA schemes were proposed under the joint constraints of outage probability requirement for PU and average/peak transmit power limit for SU.

In (7), smaller and larger θ corresponds to slower and faster decaying rate, indicating that the system can guarantee a loose and stringent violation probability requirement, respectively.

As the reader may check, the statement of the SR model above imposes no such high probability requirement; instead, even very unlikely outcomes will be explained as long as the criteria for SR explanation are met.

It may be seen from (4) that a high detection probability requirement may lead to a high false alarm probability for an individual CR if its is low, thus reducing the achievable throughput of that CR.

The probability requirement is expressed by a set of linear matrix inequalities (LMIs) that is derived by extending an existing second-order cone method; these LMIs are concurrently solved with the BLMIs of the BRL.

The probability requirement is expressed by a set of LMIs that is derived by extending an existing second-order cone method; these LMIs are to be concurrently solved with the BRL BLMIs.

Not only can successfully exclude irrelevant ingredients, the S-R model also can avoid the high probability requirement in I-S model, that's why it doesn't need to mention a recover rate in the above example.