The first one is an algorithm which finds all possible paths between two random secondary users selected as source node and destination node then returns the hop count of the shortest path between them by using the random values of node location and active state, antenna gain, and channel fading as input data.
Comparison of the observed SALI values to SALI values computed from a single randomization would not allow a robust differentiation between observed and random values (i.e., a single iteration could appear to be very similar to the observed SALI values, though highly unlikely).
These functions show correlation between random values, which, for instance, are spatial positions of heterogeneities in matrix.
The initial weights for the connections between units were set to random values between −0.1 and 0.1.
The memberships are often initialized with random values between 0 and 1, such that the constraint of the membership is satisfied.
Step 2: Based on available prior information, set {μ c, σ c }, c = 1, …, K. Step 3: Initialize the memberships for all points with random values between 0 and 1 such that the constraint on the memberships is satisfied.
At the beginning of the calculation, the 37500 (50×50×15) elements of W are fractional random values between −1 and 1.
Step 1: Initialize the membership matrix U with random values between 0 and 1.
One way to approach this discrepancy is to see it as due to the fact that in the typical Connectionist set up, the weights between nodes are initially set to random values, and are (very) slowly reset on the basis of small adjustments.
The PSO algorithm steps have been applied as illustrated in Figure 2. As it can be seen from the Figure 2; at first, the particles that represent pilot positions are initialized at random values between 0 and 127 for the system which has 128 subcarriers, and 0 and 63 for the system which has 64 subcarriers.
