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The algorithm determines a suboptimal solution subject to singular constraints.
"We are concerned with the unintended consequences or outcome if you have very specific goals, because you may end up with a suboptimal solution".
The suboptimal solution is compared with the minimum discontinuous feedback on numerical example.
An explicit suboptimal solution to the associated partial differential (HJBI) equation is applied.
Therefore, a suboptimal solution with low complexity is proposed in closed form.
In this work, the authors propose a suboptimal solution using a fixed structure in the compensator.
We develop a new method, called ε-transformation, which makes use of this complexity transition, to find a suboptimal solution.
Based on this formulation, a deflation algorithm, whose computational complexity is polynomial, is proposed to derive the suboptimal solution.
Although greedy algorithm aims at solving l0 minimization, it is more likely to fall into a suboptimal solution.
Then, we propose a novel methodology to find a suboptimal solution of the min max optimization problem.
Especially for problems requiring complex calculations to find the optimal solution, the present method can provide a straightforward suboptimal solution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com