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The procedure of algorithm is presented clearly.
The updating procedure of Algorithm 1 is known as a linear reward-inaction LR−I) [13].
On the contrary, the updating procedure of Algorithm 2 is capable of ensuring a quite flat ISL behavior.
So, from the iterative procedure of Algorithm 3.1, x k j = P H k j − 1 1 ∩ H k j − 1 2 ∩ X ( x 0 ), one has ∥ x k j − x 0 ∥ ≤ ∥ x ¯ − x 0 ∥.
Other particle filtering algorithms can be applied in a straightforward way; however, we assume bootstrap filters (i.e. the procedure of Algorithm 1) for the sake of clarity and notational simplicity.
Resorting to the coding procedure of Algorithm 2, however, all the radars increase the respective performances; in particular, we observe an average increase, in the achieved SINR values, of 1.56 dB for game G 1 and 2.66 dB for game G 2. The analysis also shows a gain in terms of ISL values, due to the game approach.
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We design optimal deterministic semi-online algorithms for every machine speed ratio s∈[1,∞), and show that idle time is required during the assignment procedure of algorithms for any s>√6/2.
The procedure of the algorithm can be summarized as algorithm 1 and algorithm 2. Our objective function maximums the system spectrum utilization.
The detail procedure of DFSA algorithm is shown in algorithm 1.
The whole procedure of the algorithm ASNSSS is explained in Algorithm 4. Furthermore, an upper bound on the number of calls to Algorithm 1 performed by the proposed algorithm can be formulated as follows.
One is mathematical functions' optimization to illustrate detailed numerical procedures of algorithms, the other is aerodynamic drag reduction of civil transport wing fuselage configuration by using virtual game.
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CEO of Professional Science Editing for Scientists @ prosciediting.com