论文标题
格拉斯曼尼亚包装：信任区域随机调整，用于基质不连贯
Grassmannian packings: Trust-region stochastic tuning for matrix incoherence
论文作者
论文摘要
我们提供了一个新的数值程序，用于构建低相干矩阵，用于矩阵不一致（TRSTMI）的信任区域随机调整，并详细介绍了该方法的CPU/GPU并行实现的实验结果。这些试验表明，当矩阵的大小较大时，这种方法比其他现有方法具有优越性。我们还提出了有关以实验结果激励和指导的最佳复杂矩阵的新猜想。
We provide a new numerical procedure for constructing low coherence matrices, Trust-Region Stochastic Tuning for Matrix Incoherence (TRSTMI) and detail the results of experiments with a CPU/GPU parallelized implementation of this method. These trials suggest the superiority of this approach over other existing methods when the size of the matrix is large. We also present new conjectures on optimal complex matrices motivated and guided by the experimental results.
