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To overcome this complexity, rule-based uncertainty propagation (RUP) as introduced by Farrance and Frenkel [6] to be combined with SMP is proposed (RUP-SMP).
To overcome this complexity, this work explores the use of the DDS distribution middleware standard on top of a software platform based on the ARINC-653 specification.
One way to overcome this complexity is providing the code with a well-structured semantics.
However, given the importance of the Shapley value and voting games, a number of approximation methods have been developed to overcome this complexity.
In order to overcome this complexity, the Next Generation Mobile Networks (NGMN) Alliance and the 3rd Generation Partnership Project (3GPP) introduced the concept of self-organizing networks (SON), which aims to automate the OAM procedures [4], reducing costs and increasing the network performance and quality of service.
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To overcome this computational complexity we derive a set of linear constraints (referred to as linearized capacity regions) which provides a much simpler formulation at a slightly reduced accuracy.
To overcome this limitation, a low-complexity estimator [5] has been developed.
To overcome this drawback, the fixed-complexity SD (FSD) [3, 4] and the K-best detector [5] have been developed.
Until recently, the best known algorithm developed to overcome this shortage with near-linear time complexity was devised by Wakita and Tsurumi (Wakita and Tsurumi, 2007).
To overcome this, we proposed a new low-complexity coplanar 5-input majority gate, which consumes less power compared to prior designs.
Nektar++ is an initiative to overcome this limitation by encapsulating the mathematical complexities of the underlying method within an efficient C++ framework, making the techniques more accessible to the broader scientific and industrial communities.
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CEO of Professional Science Editing for Scientists @ prosciediting.com