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Requirements Constraint Derived Imposed
... an underdetermined linear system can be uniquely recovered sometimes, even without imposing any additional sparsity constraints. In this paper, we derive conditions under which a unique non-negative solution for such a system can exist, based on the theory of polytopes. Furthermore, we develop the paradigm of combined sparse representations, where only a part of the coefficient vector is constrained to be non-negative, and the rest is unconstrained (general).
requirements constraint derived imposed
According to NEWIS, developing 20% wind in New England would require 4,095 miles of new lines at an estimated cost of between $11 and $15 billion. Regulatory agencies have had full knowledge of the transmission constraints and costs since 2010 and yet you have made no attempt to address this issue through policy changes or course corrections. In 2013, the public is only now becoming aware that deployment of utility-scale wind generation is stressing the& ...
At first glance, the problem appears to be a non-starter when privacy constraints are imposed: Is it even possible to find the distance between two signals without knowing what the signals are? Is it possible to determine the minimum of these ... These models encapsulate assumptions such as the privacy requirements, the behavior of participating entities and the possibility of information sharing among the participants. The privacy guarantee can be based on the& ...
On the other hand, a requirement constraint is an imposed limitation to the requirement`s context. A requirement dependency ... If we would limit credit card payments to U.S. customers only, we would be dealing with a requirement constraint. The requirement would ... as a risk control measure. If the condition occurs (whether by external factor or by design), we add the the risk control measure into the requirements matrix as a requirement derived from the original one.
... an underdetermined linear system can be uniquely recovered sometimes, even without imposing any additional sparsity constraints. In this paper, we derive conditions under which a unique non-negative solution for such a system can exist, based on the theory of polytopes. Furthermore, we develop the paradigm of combined sparse representations, where only a part of the coefficient vector is constrained to be non-negative, and the rest is unconstrained (general).
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