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Moreover, the authors formulated the system based on a Markov chain to reduce the packet loss rate.
Telatar [2] and Foschini [3] first formulated the system capacity of the MIMO systems assuming independent and identically distributed fading at different antennas.
For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS.
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The paper is organized as follows: In Section 2, we formulate the system identification problem and its relation to AEC.
First, we formulate the system as an evolution equation with unbounded output operators in a Hilbert space, using variable transformation.
Our goal is to formulate the system design problem that leads to the EW RLC code design providing distortion-optimal system performance.
Sections 2 and 3 formulate the system model and propose the joint filter design schemes for downlink and uplink of multiuser MIMO relay systems, respectively.
We formulate the system as a partially observable Markov decision process (POMDP) [21], which has successfully been used to solve the security scheduling problem [18] among others.
The first step in phase three is to formulate the system by identifying and defining the variables that will be used in the reasoning process.
In [61], artificial neural networks (ANNs) have been employed to model stability and security constraints in OPF to formulate the system security boundary (SB).
The remainder of this paper is organized as follows: In Section 2, we formulate the system model and describe concretely our resource allocation algorithm.
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