Exact(7)
We first introduce a definition of multiple stopping theory in the sum case.
When PU makes a decision, it considers the reward in the sum case.
We, then, formulate our cooperative relay selection problem as an optimal multiple stopping problem in the sum case.
Inspired by Wu and Wang's work, Wang and Wen [14] strengthened Theorem 1.1 and 1.2 to the finite sum case.
In this subsection, we solve the multiple stopping problems in the sum case by deriving the optimality equations.
For multiple stopping problem in the sum case, ({ {T_{i}^{m}} k)}) are optimal m-stopping times in the sense that for all stopping times k
Similar(50)
Recently, Wang and Wen [10] considered the partial finite sums of the reciprocal Fibonacci numbers and strengthened Theorem 1.1 and Theorem 1.2 to the finite-sum case.
case to extended negatively dependent sequences, but also from partial sums case to the maximum of partial sums.
Remark Theorem 2.2 and Corollary 2.4 are extensions of Theorem 4.1 and Corollary 4.1 in Kuczmaszewska and Lagodowski [9] to the weighted sums case, respectively.
To compute IRs, we summed cases and population between 2000 2005 and 2006 2010 and then calculated 5-year rates.
Figure 2 Gains in dBW. Figure 3 Final power allocation to source and relay in the sum power case and protocol P1. Figure 4 Final power allocation to source and relay in the sum power case for protocol P2.
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