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We conducted experiments on the network environment, to prove that our method has preferable performance.
These findings prove that our method is a valid approach for evaluating nonlinear optimal solutions.
We prove that our method fulfills the balance condition, and provide a numerical simulation.
Furthermore, we prove that our method has (O frac{1}{n})) convergence rate.
We also prove that our method has (O frac{1}{n})) convergence rate.
Simulated results prove that our method offers a simple and effective strategy for metasurface design in terahertz.
Similar(40)
The results prove that our methods outperform the existing ones in terms of the achieved localization accuracy.
In this paper, we introduce the two new classes of quasi-type methods and iteration methods to solve the problem and prove that our methods are stable under both a priori and a posteriori parameter choice rules.
All of facts prove that our methods propose an effective strategy for combining protein domain information, protein complexes information and PPI network and outperform other existing methods in function prediction.
It proves that our method may handle exception values well to some extent.
It proves that our method is effective for different values of.
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