For each, initialize the number,, of.
Initialize the number of sub-carriers N s = N s m i n.
Initialize the number of sub-carriers N s = N s m i n While {C prev (P i ) <= C new (P i )} Do { C prev (P i )=C new (P i ) Increment the number of sub-carriers with some suitable step-size s, i.e. N s = N s +s.
Initialize the number of sub-carriers N s = N s m i n While { C m p r e v ( p k, i ) < = C m n e w ( p k, i ) } Do { C m p r e v ( p k, i ) = C m n e w ( p k, i ) Increment the number of sub-carriers with a suitable step-size s, i.e. N s = N s +s.
In this case, the joint optimization problem is solved by applying the following simple iterative algorithm at each resolution level j. ➀ Initialize the iteration number it to 0. Optimize separately the three prediction filters as explained in Section 3. The resulting filters will be denoted respectively by p j ( H H, 0 ), p j ( L H, 0 ), and p j ( H L, 0 ).
Each simulation is repeated 3 times using different seeds to initialize the random number generator, and each of these simulations is compared with an independent simulation of a control population with no vaccine, but with the same human demography, baseline transmission setting, and health system.
Using different sets of ϵ values (by applying different seeds to initialize the random number generator) did not seem to affect the results.
Since the valid class number is hard to adaptively determine in advance, a component-wise expectation maximization for MMST (CEM3ST) algorithm is proposed, which can effectively initialize the valid class number.
Step 1: Initialize the parameters, including the number of the nodes, and the initialize trust value.
The detail steps of the multi-layer non-uniform clustered topology are as follows: Step 1: Initialize the parameters, including the number of the nodes, and the initialize trust value.
Step 1: Enumeration of the problem and Initialization of parameters Initialize the population size (N), number of generations (g), number of design variables (D), and limits of design variables (( U_L,L_L )).
