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As application, we construct some classes of means in one or two parameters including some standard means.
Despite its general interest in mathematical analysis, it remains true that the major interest of introducing new classes of means is the obtention of mean-inequalities.
Most of these classes of means require very specific assumptions and/or conditions on the function, which in fact restricts the range of the underlined class of means.
If f is a differentiable convex function defined on J, then Theorems 2.1 and 2.2 imply that Φ i ( x, y ; p, g, f ) ≥ 0, i = 1, 2. Now, we give mean value theorems for the functionals Φ i, i = 1, 2. These theorems enable us to define various classes of means that can be expressed in terms of linear functionals.
Similar(56)
Similar results are shown in Table 3 for a network with three classes of mean velocities.
Note that W F, min * required to achieve bit-based fairness in a network with three classes of mean velocities is same as that of two classes case.
Table 2 lists the number of slow and fast vehicles in a network with two classes of mean velocities for different choices of mean velocities.
In this section, we extend our analysis to a V2I network in which there are three classes of mean velocities: slow (S), medium (M) and fast (F).
In the following section, we derive expression for the minimum CW required, for vehicles belonging to different classes of mean velocities, to meet the desired fairness objective.
We consider a network with two classes of mean velocities: μ v S = 80 km / hr, μ v M = 120 km / hr.
The number of vehicles corresponding to different classes of mean velocities, within the coverage area of RSU, are obtained using (23) with two values of kjam : 80 and 160 veh/km/lane.
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